default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDHisao Ishibuchi
Person information
- affiliation: Southern University of Science and Technology, Shenzhen, China
- affiliation: Osaka Prefecture University, Japan
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j180]Naoki Masuyama
, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota:
Privacy-Preserving Continual Federated Clustering via Adaptive Resonance Theory. IEEE Access 12: 139692-139710 (2024)- [j179]Kangnian Lin, Genghui Li, Qingyan Li, Zhenkun Wang, Hisao Ishibuchi, Hu Zhang:
Multi-objective evolutionary algorithm with evolutionary-status-driven environmental selection. Inf. Sci. 669: 120551 (2024) - [j178]Ke Shang, Tianye Shu, Hisao Ishibuchi:
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. IEEE Trans. Evol. Comput. 28(1): 105-116 (2024) - [j177]Yiping Liu, Liting Xu, Yuyan Han, Xiangxiang Zeng, Gary G. Yen, Hisao Ishibuchi:
Evolutionary Multimodal Multiobjective Optimization for Traveling Salesman Problems. IEEE Trans. Evol. Comput. 28(2): 516-530 (2024) - [j176]Lie Meng Pang, Hisao Ishibuchi, Linjun He, Ke Shang, Longcan Chen:
Hypervolume-Based Cooperative Coevolution With Two Reference Points for Multiobjective Optimization. IEEE Trans. Evol. Comput. 28(4): 1054-1068 (2024) - [j175]Yifan Wang, Hisao Ishibuchi, Witold Pedrycz, Jihua Zhu, Xiangyong Cao, Jun Wang:
Convolutional Fuzzy Neural Networks With Random Weights for Image Classification. IEEE Trans. Emerg. Top. Comput. Intell. 8(5): 3279-3293 (2024) - [c390]Yang Nan, Hisao Ishibuchi, Tianye Shu:
Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective. CEC 2024: 1-6 - [c389]Cheng Gong, Yang Nan, Tianye Shu, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Interactive Final Solution Selection in Multi-Objective Optimization. CEC 2024: 1-9 - [c388]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Analysis of Algorithm Comparison Results on Real-World Multi-Objective Problems. CEC 2024: 1-9 - [c387]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms. CEC 2024: 1-8 - [c386]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms. GECCO 2024 - [c385]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Gradient-Guided Local Search for IGD/IGDPlus Subset Selection. GECCO 2024 - [c384]Longcan Chen, Lie Meng Pang, Qingfu Zhang, Hisao Ishibuchi:
Enhancing the Convergence Ability of Evolutionary Multi-objective Optimization Algorithms with Momentum. GECCO 2024 - [c383]Cheng Gong, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Heuristic Initialization and Knowledge-based Mutation for Large-Scale Multi-Objective 0-1 Knapsack Problems. GECCO 2024 - [c382]Cheng Gong, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Performance of NSGA-III on Multi-objective Combinatorial Optimization Problems Heavily Depends on Its Implementations. GECCO 2024 - [c381]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
New Framework of Multi-Objective Evolutionary Algorithms with Unbounded External Archive. GECCO Companion 2024: 883-902 - [c380]Rongguang Ye, Longcan Chen, Jinyuan Zhang, Hisao Ishibuchi:
Evolutionary Preference Sampling for Pareto Set Learning. GECCO 2024 - [c379]Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi:
Learning Pareto Set for Multi-Objective Continuous Robot Control. IJCAI 2024: 4920-4928 - [c378]Weiduo Liao, Ying Wei, Qirui Sun, Qingfu Zhang, Hisao Ishibuchi:
A Multi-objective Perspective Towards Improving Meta-Generalization. IJCNN 2024: 1-10 - [c377]Rongguang Ye, Lei Chen, Weiduo Liao, Jinyuan Zhang, Hisao Ishibuchi:
Data-Driven Preference Sampling for Pareto Front Learning. IJCNN 2024: 1-8 - [c376]Kenneth Zhang, Angel E. Rodriguez-Fernandez, Ke Shang, Hisao Ishibuchi, Oliver Schütze:
Hypervolume Gradient Subspace Approximation. PPSN (4) 2024: 20-35 - [c375]Cheng Gong, Ping Guo, Tianye Shu, Qingfu Zhang, Hisao Ishibuchi:
LTR-HSS: A Learning-to-Rank Based Framework for Hypervolume Subset Selection. PPSN (4) 2024: 36-51 - [c374]Cheng Gong, Lie Meng Pang, Qingfu Zhang, Hisao Ishibuchi:
Three Objectives Degrade the Convergence Ability of Dominance-Based Multi-objective Evolutionary Algorithms. PPSN (4) 2024: 52-67 - [c373]Rongguang Ye, Longcan Chen, Jinyuan Zhang, Hisao Ishibuchi:
An Unbounded Archive-Based Inverse Model in Evolutionary Multi-objective Optimization. PPSN (4) 2024: 186-201 - [c372]Lie Meng Pang, Hisao Ishibuchi, Yang Nan, Cheng Gong:
Reliability of Indicator-Based Comparison Results of Evolutionary Multi-objective Algorithms. PPSN (4) 2024: 285-298 - [c371]Hiroki Shiraishi, Rongguang Ye, Hisao Ishibuchi, Masaya Nakata:
A Variable-Length Fuzzy Set Representation for Learning Fuzzy-Classifier Systems. PPSN (3) 2024: 386-402 - [i41]Chanjuan Liu, Shike Ge, Zhihan Chen, Wenbin Pei, Enqiang Zhu, Yi Mei, Hisao Ishibuchi:
Improving Critical Node Detection Using Neural Network-based Initialization in a Genetic Algorithm. CoRR abs/2402.00404 (2024) - [i40]Rongguang Ye, Lei Chen, Weiduo Liao, Jinyuan Zhang, Hisao Ishibuchi:
Data-Driven Preference Sampling for Pareto Front Learning. CoRR abs/2404.08397 (2024) - [i39]Rongguang Ye, Longcan Chen, Jinyuan Zhang, Hisao Ishibuchi:
Evolutionary Preference Sampling for Pareto Set Learning. CoRR abs/2404.08414 (2024) - [i38]Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi:
Learning Pareto Set for Multi-Objective Continuous Robot Control. CoRR abs/2406.18924 (2024) - [i37]Javier Poyatos, Javier Del Ser, Salvador García, Hisao Ishibuchi, Daniel Molina, Isaac Triguero, Bing Xue, Xin Yao, Francisco Herrera:
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects. CoRR abs/2407.08745 (2024) - [i36]Rongguang Ye, Longcan Chen, Wei-Bin Kou, Jinyuan Zhang, Hisao Ishibuchi:
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization. CoRR abs/2408.05778 (2024) - 2023
- [j174]Takato Kinoshita, Naoki Masuyama, Yiping Liu, Yusuke Nojima, Hisao Ishibuchi:
Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-Based Clustering for Many-Objective Optimization. IEEE Access 11: 126066-126086 (2023) - [j173]Yifan Wang, Hisao Ishibuchi, Meng Joo Er, Jihua Zhu:
Unsupervised multilayer fuzzy neural networks for image clustering. Inf. Sci. 622: 682-709 (2023) - [j172]Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Benchmarking large-scale subset selection in evolutionary multi-objective optimization. Inf. Sci. 622: 755-770 (2023) - [j171]Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Multi-Label Classification via Adaptive Resonance Theory-Based Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8696-8712 (2023) - [j170]Linjun He, Auraham Camacho, Yang Nan, Anupam Trivedi, Hisao Ishibuchi, Dipti Srinivasan:
Effects of corner weight vectors on the performance of decomposition-based multiobjective algorithms. Swarm Evol. Comput. 79: 101305 (2023) - [j169]Jesús Guillermo Falcón-Cardona, Edgar Covantes Osuna, Carlos A. Coello Coello, Hisao Ishibuchi:
On the utilization of pair-potential energy functions in multi-objective optimization. Swarm Evol. Comput. 79: 101308 (2023) - [j168]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Use of Two Penalty Values in Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Trans. Cybern. 53(11): 7174-7186 (2023) - [j167]Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan:
Effects of Archive Size on Computation Time and Solution Quality for Multiobjective Optimization. IEEE Trans. Evol. Comput. 27(4): 1145-1153 (2023) - [j166]Ke Shang, Weiyu Chen, Weiduo Liao, Hisao Ishibuchi:
HV-Net: Hypervolume Approximation Based on DeepSets. IEEE Trans. Evol. Comput. 27(4): 1154-1160 (2023) - [j165]Linjun He, Ke Shang, Yang Nan, Hisao Ishibuchi, Dipti Srinivasan:
Relation Between Objective Space Normalization and Weight Vector Scaling in Decomposition-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 27(5): 1177-1191 (2023) - [j164]Wei Liu, Rui Wang, Tao Zhang, Kaiwen Li, Wenhua Li, Hisao Ishibuchi, Xiangke Liao:
Hybridization of Evolutionary Algorithm and Deep Reinforcement Learning for Multiobjective Orienteering Optimization. IEEE Trans. Evol. Comput. 27(5): 1260-1274 (2023) - [j163]Jinyuan Zhang, Linjun He, Hisao Ishibuchi:
Dual-Fuzzy-Classifier-Based Evolutionary Algorithm for Expensive Multiobjective Optimization. IEEE Trans. Evol. Comput. 27(6): 1575-1589 (2023) - [j162]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
An Improved Local Search Method for Large-Scale Hypervolume Subset Selection. IEEE Trans. Evol. Comput. 27(6): 1690-1704 (2023) - [j161]Rui Wang, Lining Xing, Maoguo Gong, Ponnuthurai Nagaratnam Suganthan, Hisao Ishibuchi:
Guest Editorial Special Issue on Deep Reinforcement Learning for Optimization: Methods and Application. IEEE Trans. Emerg. Top. Comput. Intell. 7(4): 981-982 (2023) - [c370]Yang Nan, Tianye Shu, Hisao Ishibuchi:
Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems. CEC 2023: 1-8 - [c369]Jinyuan Zhang, Linjun He, Hisao Ishibuchi:
An Improved Fuzzy Classifier-Based Evolutionary Algorithm for Expensive Multiobjective Optimization Problems with Complicated Pareto Sets. EMO 2023: 231-246 - [c368]Lie Meng Pang, Yang Nan, Hisao Ishibuchi:
Partially Degenerate Multi-objective Test Problems. EMO 2023: 277-290 - [c367]Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Performance Evaluation of Multi-objective Evolutionary Algorithms Using Artificial and Real-world Problems. EMO 2023: 333-347 - [c366]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems. EMO 2023: 391-404 - [c365]Linjun He, Yang Nan, Hisao Ishibuchi, Dipti Srinivasan:
Preference-Based Nonlinear Normalization for Multiobjective Optimization. EMO 2023: 563-577 - [c364]Yusuke Nojima, Koyo Kawano, Hajime Shimahara, Eric Vernon, Naoki Masuyama, Hisao Ishibuchi:
Fuzzy Classifiers with a Two-Stage Reject Option. FUZZ 2023: 1-6 - [c363]Yusuke Nojima, Yuto Fujii, Naoki Masuyama, Yiping Liu, Hisao Ishibuchi:
A Decomposition-based Multi-modal Multi-objective Evolutionary Algorithm with Problem Transformation into Two-objective Subproblems. GECCO Companion 2023: 399-402 - [c362]Guangyan An, Ziyu Wu, Zhilong Shen, Ke Shang, Hisao Ishibuchi:
Evolutionary Multi-Objective Deep Reinforcement Learning for Autonomous UAV Navigation in Large-Scale Complex Environments. GECCO 2023: 633-641 - [c361]Cheng Gong, Yang Nan, Lie Meng Pang, Qingfu Zhang, Hisao Ishibuchi:
Effects of Including Optimal Solutions into Initial Population on Evolutionary Multiobjective Optimization. GECCO 2023: 661-669 - [c360]Linjun He, Yang Nan, Hisao Ishibuchi, Dipti Srinivasan:
Effects of Objective Space Normalization in Multi-Objective Evolutionary Algorithms on Real-World Problems. GECCO 2023: 670-678 - [c359]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Effects of Dominance Modification on Hypervolume-based and IGD-based Performance Evaluation Results of NSGA-II. GECCO 2023: 679-687 - [c358]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets. GECCO 2023: 740-748 - [c357]Han Zhu, Ke Shang, Hisao Ishibuchi:
STHV-Net: Hypervolume Approximation based on Set Transformer. GECCO 2023: 804-812 - [c356]Weiduo Liao, Ying Wei, Mingchen Jiang, Qingfu Zhang, Hisao Ishibuchi:
Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework. NeurIPS 2023 - [c355]Yang Nan, Tianye Shu, Hisao Ishibuchi:
Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem. SMC 2023: 1154-1161 - [c354]Cheng Gong, Lie Meng Pang, Yang Nan, Hisao Ishibuchi, Qingfu Zhang:
Effects of Initialization Methods on the Performance of Multi-Objective Evolutionary Algorithms. SMC 2023: 1168-1175 - [c353]Lie Meng Pang, Yang Nan, Hisao Ishibuchi:
How to Find a Large Solution Set to Cover the Entire Pareto Front in Evolutionary Multi-Objective Optimization. SMC 2023: 1188-1194 - [c352]Ke Shang, Tianye Shu, Guotong Wu, Yang Nan, Lie Meng Pang, Hisao Ishibuchi:
Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts. SSCI 2023: 433-440 - [c351]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets. SSCI 2023: 441-448 - [c350]Guotong Wu, Tianye Shu, Ke Shang, Hisao Ishibuchi:
Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation. SSCI 2023: 449-456 - [c349]Jinyuan Zhang, Hisao Ishibuchi, Linjun He, Yang Nan:
Effects of Initialization Methods on the Performance of Surrogate-Based Multiobjective Evolutionary Algorithms. SSCI 2023: 933-940 - [c348]Cheng Gong, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Initial Populations with a Few Heuristic Solutions Significantly Improve Evolutionary Multi-Objective Combinatorial Optimization. SSCI 2023: 1398-1405 - [c347]Guotong Wu, Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Ensemble R2-based Hypervolume Contribution Approximation. SSCI 2023: 1503-1510 - [c346]Cheng Gong, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Examination of the Multimodal Nature of Multi-Objective Neural Architecture Search. SSCI 2023: 1821-1828 - [i35]Naoki Masuyama, Takanori Takebayashi, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi, Stefan Wermter:
A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning. CoRR abs/2305.01507 (2023) - [i34]Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota:
Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory. CoRR abs/2309.03487 (2023) - 2022
- [j160]Naoki Masuyama, Narito Amako, Yuna Yamada, Yusuke Nojima, Hisao Ishibuchi:
Adaptive Resonance Theory-Based Topological Clustering With a Divisive Hierarchical Structure Capable of Continual Learning. IEEE Access 10: 68042-68056 (2022) - [j159]Bin Qin, Fulai Chung, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
Fuzzy rule dropout with dynamic compensation for wide learning algorithm of TSK fuzzy classifier. Appl. Soft Comput. 127: 109410 (2022) - [j158]Jose Maria Alonso-Moral, Corrado Mencar, Hisao Ishibuchi:
Explainable and Trustworthy Artificial Intelligence [Guest Editorial]. IEEE Comput. Intell. Mag. 17(1): 14-15 (2022) - [j157]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Difficulties in Fair Performance Comparison of Multi-Objective Evolutionary Algorithms [Research Frontier]. IEEE Comput. Intell. Mag. 17(1): 86-101 (2022) - [j156]Jinyuan Zhang, Hisao Ishibuchi, Linjun He:
A classification-assisted environmental selection strategy for multiobjective optimization. Swarm Evol. Comput. 71: 101074 (2022) - [j155]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Yang Nan, Weiduo Liao:
Hypervolume-Optimal μ-Distributions on Line/Plane-Based Pareto Fronts in Three Dimensions. IEEE Trans. Evol. Comput. 26(2): 349-363 (2022) - [j154]Xinye Cai, Yushun Xiao, Zhenhua Li, Qi Sun, Hanchuan Xu, Miqing Li, Hisao Ishibuchi:
A Kernel-Based Indicator for Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 26(4): 602-615 (2022) - [j153]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Fast Greedy Subset Selection From Large Candidate Solution Sets in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(4): 750-764 (2022) - [j152]Yiming Peng, Hisao Ishibuchi:
A Diversity-Enhanced Subset Selection Framework for Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(5): 886-900 (2022) - [j151]Kaiwen Li, Tao Zhang, Rui Wang, Ling Wang, Hisao Ishibuchi:
An Evolutionary Multiobjective Knee-Based Lower Upper Bound Estimation Method for Wind Speed Interval Forecast. IEEE Trans. Evol. Comput. 26(5): 1030-1042 (2022) - [j150]Mengjun Ming, Rui Wang, Hisao Ishibuchi, Tao Zhang:
A Novel Dual-Stage Dual-Population Evolutionary Algorithm for Constrained Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(5): 1129-1143 (2022) - [j149]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Counterintuitive Experimental Results in Evolutionary Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(6): 1609-1616 (2022) - [j148]Xiongtao Zhang, Yusuke Nojima, Hisao Ishibuchi, Wenjun Hu, Shitong Wang:
Prediction by Fuzzy Clustering and KNN on Validation Data With Parallel Ensemble of Interpretable TSK Fuzzy Classifiers. IEEE Trans. Syst. Man Cybern. Syst. 52(1): 400-414 (2022) - [c345]Takato Kinoshita, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Analytical Methods to Separately Evaluate Convergence and Diversity for Multi-objective Optimization. MIC 2022: 172-186 - [c344]Hisao Ishibuchi, Yiming Peng, Lie Meng Pang:
Multi-Modal Multi-Objective Test Problems with an Infinite Number of Equivalent Pareto Sets. CEC 2022: 1-8 - [c343]Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Evolutionary Multi-Objective Multi-Tasking for Fuzzy Genetics-Based Machine Learning in Multi-Label Classification. FUZZ-IEEE 2022: 1-8 - [c342]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Difficulties in fair performance comparison of multiobjective evolutionary algorithms. GECCO Companion 2022: 937-957 - [c341]Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi, Zongying Liu:
Adaptive Resonance Theory-based Clustering for Handling Mixed Data. IJCNN 2022: 1-8 - [c340]Tianye Shu, Ke Shang, Yang Nan, Hisao Ishibuchi:
Direction Vector Selection for R2-Based Hypervolume Contribution Approximation. PPSN (2) 2022: 110-123 - [c339]Yiming Peng, Hisao Ishibuchi:
Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study. PPSN (2) 2022: 138-150 - [c338]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi:
New Solution Creation Operator in MOEA/D for Faster Convergence. PPSN (2) 2022: 234-246 - [c337]Ke Shang, Weiduo Liao, Hisao Ishibuchi:
HVC-Net: Deep Learning Based Hypervolume Contribution Approximation. PPSN (1) 2022: 414-426 - [e7]Hisao Ishibuchi, Chee-Keong Kwoh, Ah-Hwee Tan, Dipti Srinivasan, Chunyan Miao, Anupam Trivedi, Keeley A. Crockett:
IEEE Symposium Series on Computational Intelligence, SSCI 2022, Singapore, December 4-7, 2022. IEEE 2022, ISBN 978-1-6654-8768-9 [contents] - [i33]Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2201.06700 (2022) - [i32]Ke Shang, Tianye Shu, Hisao Ishibuchi:
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. CoRR abs/2201.06707 (2022) - [i31]Naoki Masuyama, Narito Amako, Yuna Yamada, Yusuke Nojima, Hisao Ishibuchi:
Adaptive Resonance Theory-based Topological Clustering with a Divisive Hierarchical Structure Capable of Continual Learning. CoRR abs/2201.10713 (2022) - [i30]Ke Shang, Weiyu Chen, Weiduo Liao, Hisao Ishibuchi:
HV-Net: Hypervolume Approximation based on DeepSets. CoRR abs/2203.02185 (2022) - [i29]Naoki Masuyama, Itsuki Tsubota, Yusuke Nojima, Hisao Ishibuchi:
Class-wise Classifier Design Capable of Continual Learning using Adaptive Resonance Theory-based Topological Clustering. CoRR abs/2203.09879 (2022) - [i28]Takato Kinoshita, Naoki Masuyama, Yiping Liu, Yusuke Nojima, Hisao Ishibuchi:
Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-based Clustering for Many-objective Optimization. CoRR abs/2204.10756 (2022) - [i27]Wei Liu, Rui Wang, Tao Zhang, Kaiwen Li, Wenhua Li, Hisao Ishibuchi:
Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization. CoRR abs/2206.10464 (2022) - [i26]Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan:
Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization. CoRR abs/2209.03100 (2022) - 2021
- [j147]Ke Shang, Hisao Ishibuchi, Linjun He, Lie Meng Pang:
A Survey on the Hypervolume Indicator in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 25(1): 1-20 (2021) - [j146]Xinye Cai, Yushun Xiao, Miqing Li, Han Hu, Hisao Ishibuchi, Xiaoping Li:
A Grid-Based Inverted Generational Distance for Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 25(1): 21-34 (2021) - [j145]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello, Michael Emmerich:
On the Effect of the Cooperation of Indicator-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(4): 681-695 (2021) - [j144]Linjun He, Hisao Ishibuchi, Anupam Trivedi, Handing Wang, Yang Nan, Dipti Srinivasan:
A Survey of Normalization Methods in Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(6): 1028-1048 (2021) - [j143]Wenhua Li, Tao Zhang, Rui Wang, Hisao Ishibuchi:
Weighted Indicator-Based Evolutionary Algorithm for Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 25(6): 1064-1078 (2021) - [j142]Suhang Gu, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
Fuzzy Style K-Plane Clustering. IEEE Trans. Fuzzy Syst. 29(6): 1518-1532 (2021) - [j141]Te Zhang, Zhaohong Deng, Hisao Ishibuchi, Lie Meng Pang:
Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data. IEEE Trans. Fuzzy Syst. 29(8): 2145-2157 (2021) - [j140]Bin Qin, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
Realizing Deep High-Order TSK Fuzzy Classifier by Ensembling Interpretable Zero-Order TSK Fuzzy Subclassifiers. IEEE Trans. Fuzzy Syst. 29(11): 3441-3455 (2021) - [c336]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Using a Genetic Algorithm-based Hyper-heuristic to Tune MOEA/D for a Set of Various Test Problems. CEC 2021: 1486-1494 - [c335]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Periodical Generation Update using an Unbounded External Archive for Multi-Objective Optimization. CEC 2021: 1912-1920 - [c334]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
A Two-stage Hypervolume Contribution Approximation Method Based on R2 Indicator. CEC 2021: 2468-2475 - [c333]Qite Yang, Zhenkun Wang, Hisao Ishibuchi:
It Is Hard to Distinguish Between Dominance Resistant Solutions and Extremely Convex Pareto Optimal Solutions. EMO 2021: 3-14 - [c332]Ke Shang, Hisao Ishibuchi, Longcan Chen, Weiyu Chen, Lie Meng Pang:
Improving the Efficiency of R2HCA-EMOA. EMO 2021: 115-125 - [c331]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Using a Genetic Algorithm-Based Hyper-Heuristic to Tune MOEA/D for a Set of Benchmark Test Problems. EMO 2021: 164-177 - [c330]Yiming Peng, Hisao Ishibuchi:
Niching Diversity Estimation for Multi-modal Multi-objective Optimization. EMO 2021: 323-334 - [c329]Jinyuan Zhang, Hisao Ishibuchi:
Multiobjective Optimization with Fuzzy Classification-Assisted Environmental Selection. EMO 2021: 580-592 - [c328]Yifan Wang, Hisao Ishibuchi, Jihua Zhu, Yaxiong Wang, Tao Dai:
Unsupervised Fuzzy Neural Network for Image Clustering. FUZZ-IEEE 2021: 1-6 - [c327]Linjun He, Hisao Ishibuchi, Dipti Srinivasan:
Metric for evaluating normalization methods in multiobjective optimization. GECCO 2021: 403-411 - [c326]Ke Shang, Hisao Ishibuchi, Yang Nan:
Distance-based subset selection revisited. GECCO 2021: 439-447 - [c325]Ke Shang, Hisao Ishibuchi, Weiyu Chen:
Greedy approximated hypervolume subset selection for many-objective optimization. GECCO 2021: 448-456 - [c324]Jinyuan Zhang, Hisao Ishibuchi, Ke Shang, Linjun He, Lie Meng Pang, Yiming Peng:
Environmental selection using a fuzzy classifier for multiobjective evolutionary algorithms. GECCO 2021: 485-492 - [c323]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Hybrid Evolutionary Algorithm for Multi-modal Multi-objective Optimization. SMC 2021: 160-167 - [c322]Ke Shang, Hisao Ishibuchi, Lie Meng Pang, Yang Nan:
Reference Point Specification for Greedy Hypervolume Subset Selection. SMC 2021: 168-175 - [c321]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization. SMC 2021: 468-475 - [c320]Lie Meng Pang, Ke Shang, Longcan Chen, Hisao Ishibuchi, Weiyu Chen:
Proposal of a New Test Problem for Large-Scale Multi- and Many-Objective Optimization. SMC 2021: 484-491 - [c319]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
Improving Local Search Hypervolume Subset Selection in Evolutionary Multi-objective Optimization. SMC 2021: 751-757 - [c318]Yiping Liu, Liting Xu, Yuyan Han, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi, Gary G. Yen:
Multi-Modal Multi-Objective Traveling Salesman Problem and its Evolutionary Optimizer. SMC 2021: 770-777 - [c317]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Periodical Weight Vector Update Using an Unbounded External Archive for Decomposition-Based Evolutionary Multi-Objective Optimization. SSCI 2021: 1-8 - [c316]Cheng Gong, Lie Meng Pang, Hisao Ishibuchi:
Initial Population Generation Method and its Effects on MOEA/D. SSCI 2021: 1-8 - [e6]Hisao Ishibuchi, Qingfu Zhang, Ran Cheng, Ke Li, Hui Li, Handing Wang, Aimin Zhou:
Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Shenzhen, China, March 28-31, 2021, Proceedings. Lecture Notes in Computer Science 12654, Springer 2021, ISBN 978-3-030-72061-2 [contents] - [i25]Yiming Peng, Hisao Ishibuchi:
Niching Diversity Estimation for Multi-modal Multi-objective Optimization. CoRR abs/2102.00383 (2021) - [i24]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Fast Greedy Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2102.00941 (2021) - [i23]Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Multi-label Classification via Adaptive Resonance Theory-based Clustering. CoRR abs/2103.01511 (2021) - [i22]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Yang Nan, Weiduo Liao:
Hypervolume-Optimal μ-Distributions on Line/Plane-based Pareto Fronts in Three Dimensions. CoRR abs/2104.09736 (2021) - [i21]Rahul Kumar Sevakula, Nishchal Kumar Verma, Hisao Ishibuchi:
On fine-tuning of Autoencoders for Fuzzy rule classifiers. CoRR abs/2106.11182 (2021) - [i20]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization. CoRR abs/2108.08453 (2021) - 2020
- [j139]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
Reverse Strategy for Non-Dominated Archiving. IEEE Access 8: 119458-119469 (2020) - [j138]Lie Meng Pang, Kai Meng Tay, Chee Peng Lim, Hisao Ishibuchi:
A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology. IEEE Access 8: 144908-144930 (2020) - [j137]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks. IEEE Access 8: 163197-163208 (2020) - [j136]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
NSGA-II With Simple Modification Works Well on a Wide Variety of Many-Objective Problems. IEEE Access 8: 190240-190250 (2020) - [j135]Ryoji Tanabe, Hisao Ishibuchi:
An easy-to-use real-world multi-objective optimization problem suite. Appl. Soft Comput. 89: 106078 (2020) - [j134]Linjun He, Ke Shang, Hisao Ishibuchi:
Simultaneous use of two normalization methods in decomposition-based multi-objective evolutionary algorithms. Appl. Soft Comput. 92: 106316 (2020) - [j133]Jian Xiong, Chao Zhang, Gang Kou, Rui Wang, Hisao Ishibuchi, Fawaz E. Alsaadi:
Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach. Complex. 2020: 3106097:1-3106097:18 (2020) - [j132]Bach Hoai Nguyen, Bing Xue, Peter Andreae, Hisao Ishibuchi, Mengjie Zhang:
Multiple Reference Points-Based Decomposition for Multiobjective Feature Selection in Classification: Static and Dynamic Mechanisms. IEEE Trans. Evol. Comput. 24(1): 170-184 (2020) - [j131]Ke Shang, Hisao Ishibuchi, Xizi Ni:
R2-Based Hypervolume Contribution Approximation. IEEE Trans. Evol. Comput. 24(1): 185-192 (2020) - [j130]Ryoji Tanabe, Hisao Ishibuchi:
A Review of Evolutionary Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 24(1): 193-200 (2020) - [j129]Yiping Liu, Hisao Ishibuchi, Naoki Masuyama, Yusuke Nojima:
Adapting Reference Vectors and Scalarizing Functions by Growing Neural Gas to Handle Irregular Pareto Fronts. IEEE Trans. Evol. Comput. 24(3): 439-453 (2020) - [j128]Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima, Naoki Masuyama:
Handling Imbalance Between Convergence and Diversity in the Decision Space in Evolutionary Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 24(3): 551-565 (2020) - [j127]Ryoji Tanabe, Hisao Ishibuchi:
A Framework to Handle Multimodal Multiobjective Optimization in Decomposition-Based Evolutionary Algorithms. IEEE Trans. Evol. Comput. 24(4): 720-734 (2020) - [j126]Ke Shang, Hisao Ishibuchi, Xizi Ni:
Erratum to "R2-Based Hypervolume Contribution Approximation". IEEE Trans. Evol. Comput. 24(4): 807 (2020) - [j125]Ke Shang, Hisao Ishibuchi:
A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization. IEEE Trans. Evol. Comput. 24(5): 839-852 (2020) - [j124]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Quality Indicators Using Approximated Optimal Distributions in a 3-D Objective Space. IEEE Trans. Evol. Comput. 24(5): 853-867 (2020) - [j123]Suhang Gu, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
A Novel Classification Method From the Perspective of Fuzzy Social Networks Based on Physical and Implicit Style Features of Data. IEEE Trans. Fuzzy Syst. 28(2): 361-375 (2020) - [c315]Yuna Yamada, Naoki Masuyama, Narito Amako, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Divisive Hierarchical Clustering Based on Adaptive Resonance Theory. CcS 2020: 1-6 - [c314]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Modified Distance-based Subset Selection for Evolutionary Multi-objective Optimization Algorithms. CEC 2020: 1-8 - [c313]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CEC 2020: 1-8 - [c312]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello:
Riesz s-energy-based Reference Sets for Multi-Objective optimization. CEC 2020: 1-8 - [c311]Ryuichi Hashimoto, Toshiki Urita, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Effects of Local Mating in Inter-task Crossover on the Performance of Decomposition-based Evolutionary Multiobjective Multitask optimization Algorithms. CEC 2020: 1-8 - [c310]Linjun He, Hisao Ishibuchi, Anupam Trivedi, Dipti Srinivasan:
Dynamic Normalization in MOEA/D for Multiobjective optimization. CEC 2020: 1-8 - [c309]Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima, Naoki Masuyama, Yuyan Han:
On the Normalization in Evolutionary Multi-Modal Multi-Objective Optimization. CEC 2020: 1-8 - [c308]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Large-scale Multi-modal Multi-objective optimization Algorithm. CEC 2020: 1-8 - [c307]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
A New Framework of Evolutionary Multi-Objective Algorithms with an Unbounded External Archive. ECAI 2020: 283-290 - [c306]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima:
Many-Objective Problems Are Not Always Difficult for Pareto Dominance-Based Evolutionary Algorithms. ECAI 2020: 291-298 - [c305]Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Multiobjective Fuzzy Genetics-Based Machine Learning for Multi-Label Classification. FUZZ-IEEE 2020: 1-8 - [c304]Hisao Ishibuchi, Hiroyuki Sato:
Evolutionary many-objective optimization. GECCO Companion 2020: 428-457 - [c303]Linjun He, Auraham Camacho, Hisao Ishibuchi:
Another difficulty of inverted triangular pareto fronts for decomposition-based multi-objective algorithms. GECCO 2020: 498-506 - [c302]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima:
Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms. GECCO 2020: 507-515 - [c301]Yang Nan, Ke Shang, Hisao Ishibuchi:
What is a good direction vector set for the R2-based hypervolume contribution approximation. GECCO 2020: 524-532 - [c300]Narito Amako, Naoki Masuyama, Chu Kiong Loo, Yusuke Nojima, Yiping Liu, Hisao Ishibuchi:
Multilayer Clustering Based on Adaptive Resonance Theory for Noisy Environments. IJCNN 2020: 1-8 - [c299]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Proposal of a Realistic Many-Objective Test Suite. PPSN (1) 2020: 201-214 - [c298]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Lukás Adam:
Hypervolume Optimal μ-Distributions on Line-Based Pareto Fronts in Three Dimensions. PPSN (2) 2020: 257-270 - [c297]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Algorithm Configurations of MOEA/D with an Unbounded External Archive. SMC 2020: 1087-1094 - [c296]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Population Size Specification for Fair Comparison of Multi-objective Evolutionary Algorithms. SMC 2020: 1095-1102 - [c295]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Numerical Analysis on Optimal Distributions of Solutions for Hypervolume Maximization. SMC 2020: 1103-1110 - [c294]Weiduo Liao, Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Parallel Implementation of MOEA/D with Parallel Weight Vectors for Feature Selection. SMC 2020: 1524-1531 - [c293]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello:
Exploiting the Trade-off between Convergence and Diversity Indicators. SSCI 2020: 141-148 - [c292]Ke Shang, Hisao Ishibuchi, Yang Nan, Weiyu Chen:
Transformation-based Hypervolume Indicator: A Framework for Designing Hypervolume Variants. SSCI 2020: 157-164 - [c291]Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Multi-label Classification Based on Adaptive Resonance Theory. SSCI 2020: 1913-1920 - [c290]Longcan Chen, Ke Shang, Hisao Ishibuchi:
Performance Comparison of Multi-Objective Evolutionary Algorithms on Simple and Difficult Many-Objective Test Problems. SSCI 2020: 2461-2468 - [i19]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multiobjective Optimization Algorithms. CoRR abs/2003.09917 (2020) - [i18]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Large-scale Multi-modal Multi-objective Optimization Algorithm. CoRR abs/2004.09838 (2020) - [i17]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Solution Subset Selection for Final Decision Making in Evolutionary Multi-Objective Optimization. CoRR abs/2006.08156 (2020) - [i16]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CoRR abs/2007.02050 (2020) - [i15]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Algorithm Configurations of MOEA/D with an Unbounded External Archive. CoRR abs/2007.13352 (2020) - [i14]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Decomposition-Based Multi-Objective Evolutionary Algorithm Design under Two Algorithm Frameworks. CoRR abs/2008.07094 (2020) - [i13]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Quality Indicators Using Approximated Optimal Distributions in a Three-dimensional Objective Space. CoRR abs/2009.12788 (2020) - [i12]Ryoji Tanabe, Hisao Ishibuchi:
An Easy-to-use Real-world Multi-objective Optimization Problem Suite. CoRR abs/2009.12867 (2020) - [i11]Ryoji Tanabe, Hisao Ishibuchi:
A Review of Evolutionary Multi-modal Multi-objective Optimization. CoRR abs/2009.13347 (2020) - [i10]Ryoji Tanabe, Hisao Ishibuchi:
A Framework to Handle Multi-modal Multi-objective Optimization in Decomposition-based Evolutionary Algorithms. CoRR abs/2009.14700 (2020) - [i9]Ryoji Tanabe, Hisao Ishibuchi:
Non-elitist Evolutionary Multi-objective Optimizers Revisited. CoRR abs/2009.14717 (2020) - [i8]Ryoji Tanabe, Hisao Ishibuchi:
A Niching Indicator-Based Multi-modal Many-objective Optimizer. CoRR abs/2010.00236 (2020) - [i7]Ryoji Tanabe, Hisao Ishibuchi:
Review and Analysis of Three Components of Differential Evolution Mutation Operator in MOEA/D-DE. CoRR abs/2010.00265 (2020) - [i6]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Control Parameters of MOEA/D Under Two Different Optimization Scenarios. CoRR abs/2010.00818 (2020) - [i5]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Evolutionary Multi-Objective Optimization Algorithm Framework with Three Solution Sets. CoRR abs/2012.07319 (2020)
2010 – 2019
- 2019
- [j122]Muhammad Atif, Siddique Latif, Rizwan Ahmad, Adnan Khalid Kiani, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas:
Soft Computing Techniques for Dependable Cyber-Physical Systems. IEEE Access 7: 72030-72049 (2019) - [j121]Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota, Yusuke Nojima, Yiping Liu:
Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning. IEEE Access 7: 76920-76936 (2019) - [j120]Hisao Ishibuchi:
Prof. Lotfi A. Zadeh [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(1): 2 (2019) - [j119]Hisao Ishibuchi:
Cashless Society [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(2): 2 (2019) - [j118]Hisao Ishibuchi:
AI and CI [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(3): 2 (2019) - [j117]Hisao Ishibuchi:
Last Editor's Remarks [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(4): 2 (2019) - [j116]Ryoji Tanabe, Hisao Ishibuchi:
Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE. Soft Comput. 23(23): 12843-12857 (2019) - [j115]Ryoji Tanabe, Hisao Ishibuchi:
A niching indicator-based multi-modal many-objective optimizer. Swarm Evol. Comput. 49: 134-146 (2019) - [j114]Zhenkun Wang, Yew-Soon Ong, Hisao Ishibuchi:
On Scalable Multiobjective Test Problems With Hardly Dominated Boundaries. IEEE Trans. Evol. Comput. 23(2): 217-231 (2019) - [j113]Wenjing Hong, Ke Tang, Aimin Zhou, Hisao Ishibuchi, Xin Yao:
A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 23(3): 525-537 (2019) - [j112]Zekang Bian, Hisao Ishibuchi, Shitong Wang:
Joint Learning of Spectral Clustering Structure and Fuzzy Similarity Matrix of Data. IEEE Trans. Fuzzy Syst. 27(1): 31-44 (2019) - [c289]Hisao Ishibuchi, Yiming Peng, Ke Shang:
A Scalable Multimodal Multiobjective Test Problem. CEC 2019: 310-317 - [c288]Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyama, Yuyan Han:
Searching for Local Pareto Optimal Solutions: A Case Study on Polygon-Based Problems. CEC 2019: 896-903 - [c287]Kanzhen Wan, Cheng He, Auraham Camacho, Ke Shang, Ran Cheng, Hisao Ishibuchi:
A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization. CEC 2019: 2018-2025 - [c286]Hisao Ishibuchi, Linjun He, Ke Shang:
Regular Pareto Front Shape is not Realistic. CEC 2019: 2034-2041 - [c285]Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
A Multiobjective Test Suite with Hexagon Pareto Fronts and Various Feasible Regions. CEC 2019: 2058-2065 - [c284]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima:
Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems. CEC 2019: 2434-2441 - [c283]Auraham Camacho, Gregorio Toscano Pulido, Ricardo Landa Becerra, Hisao Ishibuchi:
Indicator-Based Weight Adaptation for Solving Many-Objective Optimization Problems. EMO 2019: 216-228 - [c282]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima:
Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions. EMO 2019: 332-345 - [c281]Yusuke Nojima, Takafumi Fukase, Yiping Liu, Naoki Masuyama, Hisao Ishibuchi:
Constrained multiobjective distance minimization problems. GECCO 2019: 586-594 - [c280]Ryoji Tanabe, Hisao Ishibuchi:
Non-elitist evolutionary multi-objective optimizers revisited. GECCO 2019: 612-619 - [c279]Hisao Ishibuchi, Hiroyuki Sato:
Evolutionary many-objective optimization. GECCO (Companion) 2019: 614-661 - [c278]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multi-objective Optimization Algorithms. SSCI 2019: 1826-1833 - [c277]Linjun He, Yang Nan, Ke Shang, Hisao Ishibuchi:
A Study of the Naïve Objective Space Normalization Method in MOEA/D. SSCI 2019: 1834-1840 - [c276]Weiduo Liao, Ke Shang, Lie Meng Pang, Hisao Ishibuchi:
Weak Convergence Detection-based Dynamic Reference Point Specification in SMS-EMOA. SSCI 2019: 1841-1848 - [c275]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima:
Optimal Distributions of Solutions for Hypervolume Maximization on Triangular and Inverted Triangular Pareto Fronts of Four-Objective Problems. SSCI 2019: 1857-1864 - [c274]Yiming Peng, Hisao Ishibuchi, Ke Shang:
Multi-modal Multi-objective Optimization: Problem Analysis and Case Studies. SSCI 2019: 1865-1872 - [c273]Mengjun Ming, Rui Wang, Tao Zhang, Hisao Ishibuchi:
A dual-grid dual-phase strategy for constrained multi-objective optimization. SSCI 2019: 1881-1888 - [c272]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Offline Automatic Parameter Tuning of MOEA/D Using Genetic Algorithm. SSCI 2019: 1889-1897 - [c271]Naoki Masuyama, Narito Amako, Yusuke Nojima, Yiping Liu, Chu Kiong Loo, Hisao Ishibuchi:
Fast Topological Adaptive Resonance Theory Based on Correntropy Induced Metric. SSCI 2019: 2215-2221 - [c270]Ryuichi Hashimoto, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Effect of Solution Information Sharing between Tasks on the Search Ability of Evolutionary Multiobjective Multitasking Algorithms. SSCI 2019: 2671-2678 - 2018
- [j111]Kaiwen Li, Rui Wang, Tao Zhang, Hisao Ishibuchi:
Evolutionary Many-Objective Optimization: A Comparative Study of the State-of-the-Art. IEEE Access 6: 26194-26214 (2018) - [j110]Bin Xin, Lu Chen, Jie Chen, Hisao Ishibuchi, Kaoru Hirota, Bo Liu:
Interactive Multiobjective Optimization: A Review of the State-of-the-Art. IEEE Access 6: 41256-41279 (2018) - [j109]Ryoji Tanabe, Hisao Ishibuchi:
An analysis of control parameters of MOEA/D under two different optimization scenarios. Appl. Soft Comput. 70: 22-40 (2018) - [j108]Hisao Ishibuchi:
Father of Fuzzy Logic [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(1): 2 (2018) - [j107]Hisao Ishibuchi:
IEEE CIM Survey Results [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(2): 2 (2018) - [j106]Hisao Ishibuchi:
One Year in China [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(3): 2 (2018) - [j105]Hisao Ishibuchi:
CIS Sponsored Conferences in 2019 [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(4): 2 (2018) - [j104]Hisao Ishibuchi, Ryo Imada, Yu Setoguchi, Yusuke Nojima:
How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison. Evol. Comput. 26(3) (2018) - [j103]Rui Wang, Shiming Lai, Guohua Wu, Lining Xing, Ling Wang, Hisao Ishibuchi:
Multi-clustering via evolutionary multi-objective optimization. Inf. Sci. 450: 128-140 (2018) - [j102]Yaochu Jin, Kaisa Miettinen, Hisao Ishibuchi:
Guest Editorial Evolutionary Many-Objective Optimization. IEEE Trans. Evol. Comput. 22(1): 1-2 (2018) - [j101]Rui Wang, Zhongbao Zhou, Hisao Ishibuchi, Tianjun Liao, Tao Zhang:
Localized Weighted Sum Method for Many-Objective Optimization. IEEE Trans. Evol. Comput. 22(1): 3-18 (2018) - [j100]Heiner Zille, Hisao Ishibuchi, Sanaz Mostaghim, Yusuke Nojima:
A Framework for Large-Scale Multiobjective Optimization Based on Problem Transformation. IEEE Trans. Evol. Comput. 22(2): 260-275 (2018) - [j99]Manuel Chica, Raymond Chiong, Michael Kirley, Hisao Ishibuchi:
A Networked N-Player Trust Game and Its Evolutionary Dynamics. IEEE Trans. Evol. Comput. 22(6): 866-878 (2018) - [j98]Hisao Ishibuchi, Ryo Imada, Yu Setoguchi, Yusuke Nojima:
Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front. IEEE Trans. Evol. Comput. 22(6): 961-975 (2018) - [j97]Yuanpeng Zhang, Hisao Ishibuchi, Shitong Wang:
Deep Takagi-Sugeno-Kang Fuzzy Classifier With Shared Linguistic Fuzzy Rules. IEEE Trans. Fuzzy Syst. 26(3): 1535-1549 (2018) - [j96]Ta Zhou, Hisao Ishibuchi, Shitong Wang:
Stacked Blockwise Combination of Interpretable TSK Fuzzy Classifiers by Negative Correlation Learning. IEEE Trans. Fuzzy Syst. 26(6): 3327-3341 (2018) - [c269]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima:
Dynamic Specification of a Reference Point for Hypervolume Calculation in SMS-EMOA. CEC 2018: 1-8 - [c268]Hisao Ishibuchi, Takefumi Fukase, Naoki Masuyama, Yusuke Nojima:
Dual-grid model of MOEA/D for evolutionary constrained multiobjective optimization. GECCO 2018: 665-672 - [c267]Ke Shang, Hisao Ishibuchi, Min-Ling Zhang, Yiping Liu:
A new R2 indicator for better hypervolume approximation. GECCO 2018: 745-752 - [c266]Ryuichi Hashimoto, Hisao Ishibuchi, Naoki Masuyama, Yusuke Nojima:
Analysis of evolutionary multi-tasking as an island model. GECCO (Companion) 2018: 1894-1897 - [c265]Chenxu Hu, Hisao Ishibuchi:
Incorporation of a decision space diversity maintenance mechanism into MOEA/D for multi-modal multi-objective optimization. GECCO (Companion) 2018: 1898-1901 - [c264]Xizi Ni, Hisao Ishibuchi, Kanzhen Wan, Ke Shang, Chukun Zhuang:
Weight vector grid with new archive update mechanism for multi-objective optimization. GECCO (Companion) 2018: 1906-1909 - [c263]Ryoji Tanabe, Hisao Ishibuchi:
A Decomposition-Based Evolutionary Algorithm for Multi-modal Multi-objective Optimization. PPSN (1) 2018: 249-261 - [c262]Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyama, Ke Shang:
A Double-Niched Evolutionary Algorithm and Its Behavior on Polygon-Based Problems. PPSN (1) 2018: 262-273 - [c261]Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyama, Ke Shang:
Improving 1by1EA to Handle Various Shapes of Pareto Fronts. PPSN (1) 2018: 311-322 - [c260]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima:
Use of Two Reference Points in Hypervolume-Based Evolutionary Multiobjective Optimization Algorithms. PPSN (1) 2018: 384-396 - [c259]Naoki Masuyama, Yuki Tanigaki, Yusuke Nojima, Hisao Ishibuchi:
Multiobjective Evolutionary Data Mining for Performance Improvement of Evolutionary Multiobjective Optimization. SMC 2018: 745-750 - [c258]Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Performance Comparison of Multiobjective Evolutionary Algorithms on Problems with Partially Different Properties from Popular Test Suites. SMC 2018: 769-774 - [c257]Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Yusuke Nojima, Yiping Lin:
Topological Kernel Bayesian ARTMAP. WAC 2018: 1-5 - [i4]Muhammad Atif, Siddique Latif, Rizwan Ahmad, Adnan Khalid Kiani, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas:
Soft Computing Techniques for Dependable Cyber-Physical Systems. CoRR abs/1801.10472 (2018) - 2017
- [j95]Ryoji Tanabe, Hisao Ishibuchi, Akira Oyama:
Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios. IEEE Access 5: 19597-19619 (2017) - [j94]Rui Wang, Jian Xiong, Hisao Ishibuchi, Guohua Wu, Tao Zhang:
On the effect of reference point in MOEA/D for multi-objective optimization. Appl. Soft Comput. 58: 25-34 (2017) - [j93]Hisao Ishibuchi:
New Journal, New Editor-in-Chief and New VP for Publications [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(1): 2 (2017) - [j92]Hisao Ishibuchi:
Smart World [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(2): 2 (2017) - [j91]Hisao Ishibuchi:
After 30 Years of Work in Osaka [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(3): 2 (2017) - [j90]Hisao Ishibuchi:
End of Second Term as Editor-in-Chief [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(4): 3 (2017) - [j89]Zhenkun Wang, Qingfu Zhang, Hui Li, Hisao Ishibuchi, Licheng Jiao:
On the use of two reference points in decomposition based multiobjective evolutionary algorithms. Swarm Evol. Comput. 34: 89-102 (2017) - [j88]Hisao Ishibuchi, Yu Setoguchi, Hiroyuki Masuda, Yusuke Nojima:
Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes. IEEE Trans. Evol. Comput. 21(2): 169-190 (2017) - [j87]Ta Zhou, Hisao Ishibuchi, Shitong Wang:
Stacked-Structure-Based Hierarchical Takagi-Sugeno-Kang Fuzzy Classification Through Feature Augmentation. IEEE Trans. Emerg. Top. Comput. Intell. 1(6): 421-436 (2017) - [j86]Antoaneta Serguieva, Hisao Ishibuchi, Ronald R. Yager, Vasile Palade:
Guest Editorial Special Issue on Fuzzy Techniques in Financial Modeling and Simulation. IEEE Trans. Fuzzy Syst. 25(2): 245-248 (2017) - [j85]Xiaoqing Gu, Fu-Lai Chung, Hisao Ishibuchi, Shitong Wang:
Imbalanced TSK Fuzzy Classifier by Cross-Class Bayesian Fuzzy Clustering and Imbalance Learning. IEEE Trans. Syst. Man Cybern. Syst. 47(8): 2005-2020 (2017) - [c256]Hisao Ishibuchi, Ryo Imada, Yu Setoguchi, Yusuke Nojima:
Hypervolume Subset Selection for Triangular and Inverted Triangular Pareto Fronts of Three-Objective Problems. FOGA 2017: 95-110 - [c255]Yusuke Nojima, Koki Arahari, Shuji Takemura, Hisao Ishibuchi:
Multiobjective fuzzy genetics-based machine learning based on MOEA/D with its modifications. FUZZ-IEEE 2017: 1-6 - [c254]Bach Hoai Nguyen, Bing Xue, Hisao Ishibuchi, Peter Andreae, Mengjie Zhang:
Multiple reference points MOEA/D for feature selection. GECCO (Companion) 2017: 157-158 - [c253]Hisao Ishibuchi, Ryo Imada, Yu Setoguchi, Yusuke Nojima:
Reference point specification in hypervolume calculation for fair comparison and efficient search. GECCO 2017: 585-592 - [c252]Yusuke Nojima, Yuki Tanigaki, Hisao Ishibuchi:
Multiobjective data mining from solutions by evolutionary multiobjective optimization. GECCO 2017: 617-624 - [c251]Yusuke Nojima, Shuji Takemura, Kazuhiro Watanabe, Hisao Ishibuchi:
Michigan-style fuzzy GBML with (1+1)-ES generation update and multi-pattern rule generation. IFSA-SCIS 2017: 1-6 - [c250]Yuki Tanigaki, Yusuke Nojima, Hisao Ishibuchi:
Performance comparison of EMO algorithms on test problems with different search space shape. IFSA-SCIS 2017: 1-6 - [c249]Ken Doi, Ryo Imada, Yusuke Nojima, Hisao Ishibuchi:
Use of Inverted Triangular Weight Vectors in Decomposition-Based Many-Objective Algorithms. SEAL 2017: 321-333 - [c248]Hisao Ishibuchi, Ryo Imada, Ken Doi, Yusuke Nojima:
Use of inverted triangular weight vectors in decomposition-based multiobjective algorithms. SMC 2017: 373-378 - [i3]Yuan Yuan, Yew-Soon Ong, Liang Feng, A. Kai Qin, Abhishek Gupta, Bingshui Da, Qingfu Zhang, Kay Chen Tan, Yaochu Jin, Hisao Ishibuchi:
Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results. CoRR abs/1706.02766 (2017) - 2016
- [j84]Hisao Ishibuchi:
Second Term as Editor-in-Chief [Editor's Remarks]. IEEE Comput. Intell. Mag. 11(1): 2 (2016) - [j83]Hisao Ishibuchi:
CIS Distinguished Lecturers Program Editor's Remarks. IEEE Comput. Intell. Mag. 11(2): 2 (2016) - [j82]Hisao Ishibuchi:
Power of a Single Photo in the Big Data Era [Editor's Remarks]. IEEE Comput. Intell. Mag. 11(3): 2 (2016) - [j81]Hisao Ishibuchi:
IEEE Standards [Editor's Remarks]. IEEE Comput. Intell. Mag. 11(4): 2 (2016) - [j80]Kaname Narukawa, Yu Setoguchi, Yuki Tanigaki, Markus Olhofer, Bernhard Sendhoff, Hisao Ishibuchi:
Preference representation using Gaussian functions on a hyperplane in evolutionary multi-objective optimization. Soft Comput. 20(7): 2733-2757 (2016) - [j79]Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
Pareto Fronts of Many-Objective Degenerate Test Problems. IEEE Trans. Evol. Comput. 20(5): 807-813 (2016) - [j78]Zhaohong Deng, Yizhang Jiang, Fu-Lai Chung, Hisao Ishibuchi, Kup-Sze Choi, Shitong Wang:
Transfer Prototype-Based Fuzzy Clustering. IEEE Trans. Fuzzy Syst. 24(5): 1210-1232 (2016) - [j77]Zhaohong Deng, Yizhang Jiang, Hisao Ishibuchi, Kup-Sze Choi, Shitong Wang:
Enhanced Knowledge-Leverage-Based TSK Fuzzy System Modeling for Inductive Transfer Learning. ACM Trans. Intell. Syst. Technol. 8(1): 11:1-11:21 (2016) - [c247]Takahiko Sudo, Kazushi Goto, Yusuke Nojima, Hisao Ishibuchi:
Further analysis on strange evolution behavior of 7-bit binary string strategies in iterated prisoner's dilemma game. CEC 2016: 335-342 - [c246]Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
Sensitivity of performance evaluation results by inverted generational distance to reference points. CEC 2016: 1107-1114 - [c245]Hisao Ishibuchi, Ken Doi, Yusuke Nojima:
Characteristics of many-objective test problems and penalty parameter specification in MOEA/D. CEC 2016: 1115-1122 - [c244]Hisao Ishibuchi, Yu Setoguchi, Hiroyuki Masuda, Yusuke Nojima:
How to compare many-objective algorithms under different settings of population and archive sizes. CEC 2016: 1149-1156 - [c243]Yusuke Nojima, Hisao Ishibuchi:
Effects of parallel distributed implementation on the search performance of Pittsburgh-style genetics-based machine learning algorithms. CEC 2016: 2193-2200 - [c242]Yuki Tanigaki, Yusuke Nojima, Hisao Ishibuchi:
Meta-optimization based multi-objective test problem generation using WFG toolkit. CEC 2016: 2768-2775 - [c241]Hiroyuki Masuda, Yusuke Nojima, Hisao Ishibuchi:
Common properties of scalable multiobjective problems and a new framework of test problems. CEC 2016: 3011-3018 - [c240]Hisao Ishibuchi, Ryo Imada, Yu Setoguchi, Yusuke Nojima:
Performance comparison of NSGA-II and NSGA-III on various many-objective test problems. CEC 2016: 3045-3052 - [c239]Yusuke Nojima, Hisao Ishibuchi:
Multiobjective fuzzy genetics-based machine learning with a reject option. FUZZ-IEEE 2016: 1405-1412 - [c238]Heiner Zille, Hisao Ishibuchi, Sanaz Mostaghim, Yusuke Nojima:
Weighted Optimization Framework for Large-scale Multi-objective Optimization. GECCO (Companion) 2016: 83-84 - [c237]Binhui Chen, Rong Qu, Ruibin Bai, Hisao Ishibuchi:
An Investigation on Compound Neighborhoods for VRPTW. ICORES (Selected Papers) 2016: 3-19 - [c236]Binhui Chen, Rong Qu, Ruibin Bai, Hisao Ishibuchi:
A Variable Neighbourhood Search Algorithm with Compound Neighbourhoods for VRPTW. ICORES 2016: 25-35 - [c235]Hisao Ishibuchi, Ken Doi, Yusuke Nojima:
Use of Piecewise Linear and Nonlinear Scalarizing Functions in MOEA/D. PPSN 2016: 503-513 - [c234]Takahiro Funakoshi, Yusuke Nojima, Hisao Ishibuchi:
Effects of Different Implementations of a Real Random Number Generator on the Search Behavior of Multiobjective Evolutionary Algorithms. SCIS&ISIS 2016: 172-177 - [c233]Hisao Ishibuchi, Ken Doi, Yusuke Nojima:
Reference point specification in MOEA/D for multi-objective and many-objective problems. SMC 2016: 4015-4020 - [c232]Rui Wang, Hisao Ishibuchi, Yan Zhang, Xiaojun Zheng, Tao Zhang:
On the effect of localized PBI method in MOEA/D for multi-objective optimization. SSCI 2016: 1-8 - [c231]Heiner Zille, Hisao Ishibuchi, Sanaz Mostaghim, Yusuke Nojima:
Mutation operators based on variable grouping for multi-objective large-scale optimization. SSCI 2016: 1-8 - 2015
- [j76]Hisao Ishibuchi:
Top Three News Stories on IEEE CIM in 2014 [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(1): 2 (2015) - [j75]Hisao Ishibuchi:
Traveling with My Laptop [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(2): 2 (2015) - [j74]Hisao Ishibuchi:
WCCI 2006 and WCCI 2016 in Vancouver [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(3): 2 (2015) - [j73]Hisao Ishibuchi:
Talking with Young Researchers [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(4): 2 (2015) - [j72]Yizhang Jiang, Korris Fu-Lai Chung, Hisao Ishibuchi, Zhaohong Deng, Shitong Wang:
Multitask TSK Fuzzy System Modeling by Mining Intertask Common Hidden Structure. IEEE Trans. Cybern. 45(3): 548-561 (2015) - [j71]Xin Gu, Fu-Lai Chung, Hisao Ishibuchi, Shitong Wang:
Multitask Coupled Logistic Regression and its Fast Implementation for Large Multitask Datasets. IEEE Trans. Cybern. 45(9): 1953-1966 (2015) - [j70]Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima:
Behavior of Multiobjective Evolutionary Algorithms on Many-Objective Knapsack Problems. IEEE Trans. Evol. Comput. 19(2): 264-283 (2015) - [c230]Yusuke Nojima, Yuji Takahashi, Hisao Ishibuchi:
Application of Parallel Distributed Implementation to Multiobjective Fuzzy Genetics-Based Machine Learning. ACIIDS (1) 2015: 462-471 - [c229]Yuji Takahashi, Yusuke Nojima, Hisao Ishibuchi:
Rotation effects of objective functions in parallel distributed multiobjective fuzzy genetics-based machine learning. ASCC 2015: 1-6 - [c228]Yuki Tanigaki, Hiroyuki Masuda, Yu Setoguchi, Yusuke Nojima, Hisao Ishibuchi:
Algorithm structure optimization by choosing operators in multiobjective genetic local search. CEC 2015: 854-861 - [c227]Takahiko Sudo, Kazushi Goto, Yusuke Nojima, Hisao Ishibuchi:
Effects of ensemble action selection with different usage of player's memory resource on the evolution of cooperative strategies for iterated prisoner's dilemma game. CEC 2015: 1505-1512 - [c226]Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
Comparing solution sets of different size in evolutionary many-objective optimization. CEC 2015: 2859-2866 - [c225]Yusuke Nojima, Kazuhiro Watanabe, Hisao Ishibuchi:
Effects of heuristic rule generation from multiple patterns in multiobjective fuzzy genetics-Based machine learning. CEC 2015: 2996-3003 - [c224]Takahiko Sudo, Kazushi Goto, Yusuke Nojima, Hisao Ishibuchi:
Strange evolution behavior of 7-bit binary string strategies in iterated prisoner's dilemma game. CEC 2015: 3346-3353 - [c223]Hisao Ishibuchi, Hiroyuki Masuda, Yuki Tanigaki, Yusuke Nojima:
Modified Distance Calculation in Generational Distance and Inverted Generational Distance. EMO (2) 2015: 110-125 - [c222]Yu Setoguchi, Kaname Narukawa, Hisao Ishibuchi:
A Knee-Based EMO Algorithm with an Efficient Method to Update Mobile Reference Points. EMO (1) 2015: 202-217 - [c221]Hisao Ishibuchi, Yusuke Nojima:
Handling a training dataset as a black-box model for privacy preserving in fuzzy GBML algorithms. FUZZ-IEEE 2015: 1-8 - [c220]Yusuke Nojima, Kazuhiro Watanabe, Hisao Ishibuchi:
Simple modifications on heuristic rule generation and rule evaluation in Michigan-style fuzzy genetics-based machine learning. FUZZ-IEEE 2015: 1-8 - [c219]Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
A Study on Performance Evaluation Ability of a Modified Inverted Generational Distance Indicator. GECCO 2015: 695-702 - [c218]Hisao Ishibuchi, Ken Doi, Hiroyuki Masuda, Yusuke Nojima:
Relation Between Weight Vectors and Solutions in MOEA/D. SSCI 2015: 861-868 - [c217]Yusuke Nojima, Kazuhiro Watanabe, Hisao Ishibuchi:
Variants of heuristic rule generation from multiple patterns in Michigan-style fuzzy genetics-based machine learning. TAAI 2015: 427-432 - [p15]Hisao Ishibuchi, Yusuke Nojima:
Multiobjective Genetic Fuzzy Systems. Handbook of Computational Intelligence 2015: 1479-1498 - [e5]Adnan Yazici, Nikhil R. Pal, Uzay Kaymak, Trevor Martin, Hisao Ishibuchi, Chin-Teng Lin, João M. C. Sousa, Bülent Tütmez:
2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, Istanbul, Turkey, August 2-5, 2015. IEEE 2015, ISBN 978-1-4673-7428-6 [contents] - 2014
- [j69]Huynh Thi Thanh Binh, Lam Thu Bui, Nguyen Sy Thai Ha, Hisao Ishibuchi:
A multi-objective approach for solving the survivable network design problem with simultaneous unicast and anycast flows. Appl. Soft Comput. 24: 1145-1154 (2014) - [j68]Hisao Ishibuchi:
Message from the New Editor-in-Chief [Editor's Remarks]. IEEE Comput. Intell. Mag. 9(1): 2 (2014) - [j67]Hisao Ishibuchi:
Big Data Era [Editor's Remarks]. IEEE Comput. Intell. Mag. 9(3): 2-11 (2014) - [j66]Min Xu, Hisao Ishibuchi, Xin Gu, Shitong Wang:
Dm-KDE: dynamical kernel density estimation by sequences of KDE estimators with fixed number of components over data streams. Frontiers Comput. Sci. 8(4): 563-580 (2014) - [j65]Chin Hooi Tan, Keem Siah Yap, Hisao Ishibuchi, Yusuke Nojima, Hwa Jen Yap:
Application of Fuzzy Inference Rules to Early Semi-automatic Estimation of Activity Duration in Software Project Management. IEEE Trans. Hum. Mach. Syst. 44(5): 678-688 (2014) - [c216]Giovanni Acampora, Hisao Ishibuchi, Autilia Vitiello:
A comparison of multi-objective evolutionary algorithms for the ontology meta-matching problem. IEEE Congress on Evolutionary Computation 2014: 413-420 - [c215]Takahiko Sudo, Yusuke Nojima, Hisao Ishibuchi:
Effects of ensemble action selection on the evolution of iterated prisoner's dilemma game strategies. IEEE Congress on Evolutionary Computation 2014: 1195-1201 - [c214]Hiroyuki Masuda, Yusuke Nojima, Hisao Ishibuchi:
Visual examination of the behavior of EMO algorithms for many-objective optimization with many decision variables. IEEE Congress on Evolutionary Computation 2014: 2633-2640 - [c213]Hisao Ishibuchi, Hiroyuki Masuda, Yuki Tanigaki, Yusuke Nojima:
Difficulties in specifying reference points to calculate the inverted generational distance for many-objective optimization problems. MCDM 2014: 170-177 - [c212]Hisao Ishibuchi, Hiroyuki Masuda, Yuki Tanigaki, Yusuke Nojima:
Review of coevolutionary developments of evolutionary multi-objective and many-objective algorithms and test problems. MCDM 2014: 178-184 - [c211]Yuji Takahashi, Yusuke Nojima, Hisao Ishibuchi:
Hybrid fuzzy genetics-based machine learning with entropy-based inhomogeneous interval discretization. FUZZ-IEEE 2014: 1512-1517 - [c210]Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
Meta-level multi-objective formulations of set optimization for multi-objective optimization problems: multi-reference point approach to hypervolume maximization. GECCO (Companion) 2014: 89-90 - [c209]Kaname Narukawa, Yuki Tanigaki, Hisao Ishibuchi:
Evolutionary many-objective optimization using preference on hyperplane. GECCO (Companion) 2014: 91-92 - [c208]Hisao Ishibuchi, Takahiko Sudo, Yusuke Nojima:
Archive Management in Interactive Evolutionary Computation with Minimum Requirement for Human User's Fitness Evaluation Ability. ICAISC (1) 2014: 360-371 - [c207]Hisao Ishibuchi, Yuki Tanigaki, Hiroyuki Masuda, Yusuke Nojima:
Distance-Based Analysis of Crossover Operators for Many-Objective Knapsack Problems. PPSN 2014: 600-610 - [c206]Yuki Tanigaki, Kaname Narukawa, Yusuke Nojima, Hisao Ishibuchi:
Preference-based NSGA-II for many-objective knapsack problems. SCIS&ISIS 2014: 637-642 - [c205]Yusuke Nojima, Yuji Takahashi, Hisao Ishibuchi:
Genetic lateral tuning of membership functions as post-processing for hybrid fuzzy genetics-based machine learning. SCIS&ISIS 2014: 667-672 - [c204]Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
Selecting a small number of non-dominated solutions to be presented to the decision maker. SMC 2014: 3816-3821 - [e4]Grant Dick, Will N. Browne, Peter A. Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang:
Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings. Lecture Notes in Computer Science 8886, Springer 2014, ISBN 978-3-319-13562-5 [contents] - 2013
- [j64]Rafael Alcalá, Yusuke Nojima, Hisao Ishibuchi, Francisco Herrera:
Special Issue on "Evolutionary Fuzzy Systems" EFSs. Knowl. Based Syst. 54: 1-2 (2013) - [j63]Hisao Ishibuchi, Yusuke Nojima:
Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design. Knowl. Based Syst. 54: 22-31 (2013) - [j62]Michela Fazzolari, Rafael Alcalá, Yusuke Nojima, Hisao Ishibuchi, Francisco Herrera:
A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions. IEEE Trans. Fuzzy Syst. 21(1): 45-65 (2013) - [j61]Hisao Ishibuchi, Shingo Mihara, Yusuke Nojima:
Parallel Distributed Hybrid Fuzzy GBML Models With Rule Set Migration and Training Data Rotation. IEEE Trans. Fuzzy Syst. 21(2): 355-368 (2013) - [j60]Zhaohong Deng, Yizhang Jiang, Fu-Lai Chung, Hisao Ishibuchi, Shitong Wang:
Knowledge-Leverage-Based Fuzzy System and Its Modeling. IEEE Trans. Fuzzy Syst. 21(4): 597-609 (2013) - [c203]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Learning from multiple data sets with different missing attributes and privacy policies: Parallel distributed fuzzy genetics-based machine learning approach. IEEE BigData 2013: 63-70 - [c202]Hisao Ishibuchi, Takahiko Sudo, Koichiro Hoshino, Yusuke Nojima:
Evolution of cooperative strategies for iterated prisoner's dilemma on networks. CASoN 2013: 32-37 - [c201]Hisao Ishibuchi, Masakazu Yamane, Naoya Akedo, Yusuke Nojima:
Many-objective and many-variable test problems for visual examination of multiobjective search. IEEE Congress on Evolutionary Computation 2013: 1491-1498 - [c200]Hisao Ishibuchi, Yuki Tanigaki, Naoya Akedo, Yusuke Nojima:
How to strike a balance between local search and global search in multiobjective memetic algorithms for multiobjective 0/1 knapsack problems. IEEE Congress on Evolutionary Computation 2013: 1643-1650 - [c199]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Effects of duplicated objectives in many-objective optimization problems on the search behavior of hypervolume-based evolutionary algorithms. MCDM 2013: 25-32 - [c198]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Difficulty in Evolutionary Multiobjective Optimization of Discrete Objective Functions with Different Granularities. EMO 2013: 230-245 - [c197]Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima:
Relation between Neighborhood Size and MOEA/D Performance on Many-Objective Problems. EMO 2013: 459-474 - [c196]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Rule weight update in parallel distributed fuzzy genetics-based machine learning with data rotation. FUZZ-IEEE 2013: 1-8 - [c195]Michela Fazzolari, Rafael Alcalá, Yusuke Nojima, Hisao Ishibuchi, Francisco Herrera:
Improving a fuzzy association rule-based classification model by granularity learning based on heuristic measures over multiple granularities. GEFS 2013: 44-51 - [c194]Yusuke Nojima, Hisao Ishibuchi:
Multiobjective genetic fuzzy rule selection with fuzzy relational rules. GEFS 2013: 60-67 - [c193]Hisao Ishibuchi, Yusuke Nojima:
Difficulties in choosing a single final classifier from non-dominated solutions in multiobjective fuzzy genetics-based machine learning. IFSA/NAFIPS 2013: 1203-1208 - [c192]Hisao Ishibuchi, Koichiro Hoshino, Yusuke Nojima:
Neighborhood Specification for Game Strategy Evolution in a Spatial Iterated Prisoner's Dilemma Game. LION 2013: 215-230 - [c191]Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima:
A Study on the Specification of a Scalarizing Function in MOEA/D for Many-Objective Knapsack Problems. LION 2013: 231-246 - [c190]Hisao Ishibuchi, Takahiko Sudo, Koichiro Hoshino, Yusuke Nojima:
Effects of the Number of Opponents on the Evolution of Cooperation in the Iterated Prisoner's Dilemma. SMC 2013: 2001-2006 - 2012
- [j59]Rafael Alcalá, Yusuke Nojima, Hisao Ishibuchi, Francisco Herrera:
Special Issue on Evolutionary Fuzzy Systems. Int. J. Comput. Intell. Syst. 5(2): 209-211 (2012) - [c189]Hisao Ishibuchi, Koichiro Hoshino, Yusuke Nojima:
Strategy evolution in a spatial IPD game where each agent is not allowed to play against itself. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c188]Hisao Ishibuchi, Koichiro Hoshino, Yusuke Nojima:
Evolution of strategies in a spatial IPD game with a number of different representation schemes. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c187]Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi:
Application of parallel distributed genetics-based machine learning to imbalanced data sets. FUZZ-IEEE 2012: 1-6 - [c186]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Effects of discrete objective functions with different granularities on the search behavior of EMO algorithms. GECCO 2012: 481-488 - [c185]Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima:
Recombination of Similar Parents in SMS-EMOA on Many-Objective 0/1 Knapsack Problems. PPSN (2) 2012: 132-142 - [c184]Masakazu Yamane, Akihito Ueda, Naoshi Tadokoro, Yusuke Nojima, Hisao Ishibuchi:
Comparison of different fitness functions in genetic fuzzy rule selection. SCIS&ISIS 2012: 1046-1051 - [c183]Hisao Ishibuchi, Masakazu Yamane, Naoya Akedo, Yusuke Nojima:
Two-objective solution set optimization to maximize hypervolume and decision space diversity in multiobjective optimization. SCIS&ISIS 2012: 1871-1876 - [c182]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Ensemble Fuzzy Rule-Based Classifier Design by Parallel Distributed Fuzzy GBML Algorithms. SEAL 2012: 93-103 - [p14]Andrzej Jaszkiewicz, Hisao Ishibuchi, Qingfu Zhang:
Multiobjective Memetic Algorithms. Handbook of Memetic Algorithms 2012: 201-217 - [e3]Lam Thu Bui, Yew-Soon Ong, Nguyen Xuan Hoai, Hisao Ishibuchi, Ponnuthurai Nagaratnam Suganthan:
Simulated Evolution and Learning - 9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19, 2012. Proceedings. Lecture Notes in Computer Science 7673, Springer 2012, ISBN 978-3-642-34858-7 [contents] - 2011
- [j58]Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima:
Design of Linguistically Interpretable Fuzzy Rule-Based Classifiers: A Short Review and Open Questions. J. Multiple Valued Log. Soft Comput. 17(2-3): 101-134 (2011) - [j57]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Implementation of cellular genetic algorithms with two neighborhood structures for single-objective and multi-objective optimization. Soft Comput. 15(9): 1749-1767 (2011) - [j56]Yusuke Nojima, Rafael Alcalá, Hisao Ishibuchi, Francisco Herrera:
Special issue on evolutionary fuzzy systems. Soft Comput. 15(12): 2299-2301 (2011) - [j55]Rafael Alcalá, Yusuke Nojima, Francisco Herrera, Hisao Ishibuchi:
Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions. Soft Comput. 15(12): 2303-2318 (2011) - [j54]Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima:
Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. Soft Comput. 15(12): 2415-2434 (2011) - [j53]Hisao Ishibuchi, Hiroyuki Ohyanagi, Yusuke Nojima:
Evolution of Strategies With Different Representation Schemes in a Spatial Iterated Prisoner's Dilemma Game. IEEE Trans. Comput. Intell. AI Games 3(1): 67-82 (2011) - [c181]Hisao Ishibuchi, Naoya Akedo, Hiroyuki Ohyanagi, Yusuke Nojima:
Behavior of EMO algorithms on many-objective optimization problems with correlated objectives. IEEE Congress on Evolutionary Computation 2011: 1465-1472 - [c180]Hisao Ishibuchi, Keisuke Takahashi, Kouichirou Hoshino, Junpei Maeda, Yusuke Nojima:
Effects of configuration of agents with different strategy representations on the evolution of cooperative behavior in a spatial IPD game. CIG 2011: 313-320 - [c179]Hisao Ishibuchi, Naoya Akedo, Hiroyuki Ohyanagi, Yasuhiro Hitotsuyanagi, Yusuke Nojima:
Many-objective test problems with multiple Pareto optimal regions in a decision space. MCDM 2011: 113-120 - [c178]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Hiroyuki Ohyanagi, Yusuke Nojima:
Effects of the Existence of Highly Correlated Objectives on the Behavior of MOEA/D. EMO 2011: 166-181 - [c177]Yusuke Nojima, Shinya Nishikawa, Hisao Ishibuchi:
A meta-fuzzy classifier for specifying appropriate fuzzy partitions by genetic fuzzy rule selection with data complexity measures. FUZZ-IEEE 2011: 264-271 - [c176]Hisao Ishibuchi, Yusuke Nojima:
Toward quantitative definition of explanation ability of fuzzy rule-based classifiers. FUZZ-IEEE 2011: 549-556 - [c175]Hisao Ishibuchi, Naoya Akedo, Yusuke Nojima:
A many-objective test problem for visually examining diversity maintenance behavior in a decision space. GECCO 2011: 649-656 - [c174]Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima:
Double cross-validation for performance evaluation of multi-objective genetic fuzzy systems. GEFS 2011: 31-38 - [c173]Yusuke Nojima, Hisao Ishibuchi:
Mobile Robot Controller Design by Evolutionary Multiobjective Optimization in Multiagent Environments. ICIRA (2) 2011: 515-524 - [c172]Hisao Ishibuchi, Shingo Mihara, Yusuke Nojima:
Training Data Subdivision and Periodical Rotation in Hybrid Fuzzy Genetics-Based Machine Learning. ICMLA (1) 2011: 229-234 - [e2]Xue-wen Chen, Tharam S. Dillon, Hisao Ishibuchi, Jian Pei, Haixun Wang, M. Arif Wani:
10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 1: Main Conference. IEEE Computer Society 2011, ISBN 978-0-7695-4607-0 [contents] - [e1]Xue-wen Chen, Tharam S. Dillon, Hisao Ishibuchi, Jian Pei, Haixun Wang, M. Arif Wani:
10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 2: Special Sessions and Workshop. IEEE Computer Society 2011 [contents] - 2010
- [j52]Hisao Ishibuchi:
IEEE CIS VP-Technical Activities Vision Statement [Society Briefs]. IEEE Comput. Intell. Mag. 5(2): 6 (2010) - [j51]Ke Tang, Kay Chen Tan, Hisao Ishibuchi:
Guest editorial: Memetic Algorithms for Evolutionary Multi-Objective Optimization. Memetic Comput. 2(1): 1 (2010) - [j50]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Diversity Improvement by Non-Geometric Binary Crossover in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 14(6): 985-998 (2010) - [c171]Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi:
Ensemble classifier design by parallel distributed implementation of genetic fuzzy rule selection for large data sets. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c170]Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima:
Effects of fine fuzzy partitions on the generalization ability of evolutionary multi-objective fuzzy rule-based classifiers. FUZZ-IEEE 2010: 1-8 - [c169]Yusuke Nojima, Yutaka Kaisho, Hisao Ishibuchi:
Accuracy improvement of genetic fuzzy rule selection with candidate rule addition and membership tuning. FUZZ-IEEE 2010: 1-8 - [c168]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Simultaneous use of different scalarizing functions in MOEA/D. GECCO 2010: 519-526 - [c167]Hisao Ishibuchi, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima:
Indicator-based evolutionary algorithm with hypervolume approximation by achievement scalarizing functions. GECCO 2010: 527-534 - [c166]Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima:
Simple changes in problem formulations make a difference in multiobjective genetic fuzzy systems. GEFS 2010: 3-8 - [c165]Yusuke Nojima, Hisao Ishibuchi, Shingo Mihara:
Use of very small training data subsets in parallel distributed genetic fuzzy rule selection. GEFS 2010: 27-32 - [c164]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nakashima, Yusuke Nojima:
Multiobjectivization from two objectives to four objectives in evolutionary multi-objective optimization algorithms. NaBIC 2010: 502-507 - [c163]Shinya Nishikawa, Yusuke Nojima, Hisao Ishibuchi:
Appropriate granularity specification for fuzzy classifier design by data complexity measures. NaBIC 2010: 691-696 - [c162]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima:
Many-Objective Test Problems to Visually Examine the Behavior of Multiobjective Evolution in a Decision Space. PPSN (2) 2010: 91-100 - [c161]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yoshihiko Wakamatsu, Yusuke Nojima:
How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms. PPSN (1) 2010: 516-525 - [c160]Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi:
Parallel Distributed Implementation of Genetics-Based Machine Learning for Fuzzy Classifier Design. SEAL 2010: 309-318
2000 – 2009
- 2009
- [j49]Noritaka Tsukamoto, Yusuke Nojima, Hisao Ishibuchi:
Effects of nongeometric binary crossover on multiobjective 0/1 knapsack problems. Artif. Life Robotics 13(2): 434-437 (2009) - [j48]Yoshihiro Hamada, Yusuke Nojima, Hisao Ishibuchi:
Use of multi-objective genetic rule selection for examining the effectiveness of inter-vehicle communication in traffic simulations. Artif. Life Robotics 14(3): 410-413 (2009) - [j47]Hiroyuki Ohyanagi, Yoshihiko Wakamatsu, Yusuke Nakashima, Yusuke Nojima, Hisao Ishibuchi:
Evolution of cooperative behavior among heterogeneous agents with different strategy representations in an iterated prisoner's dilemma game. Artif. Life Robotics 14(3): 414-417 (2009) - [j46]Yusuke Nojima, Hisao Ishibuchi:
Incorporation of user preference into multi-objective genetic fuzzy rule selection for pattern classification problems. Artif. Life Robotics 14(3): 418-421 (2009) - [j45]Yusuke Nojima, Hisao Ishibuchi, Isao Kuwajima:
Parallel distributed genetic fuzzy rule selection. Soft Comput. 13(5): 511-519 (2009) - [j44]Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi:
Special issue on emerging trends in soft computing: memetic algorithms. Soft Comput. 13(8-9): 739-740 (2009) - [j43]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima:
Use of biased neighborhood structures in multiobjective memetic algorithms. Soft Comput. 13(8-9): 795-810 (2009) - [c159]Hisao Ishibuchi, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima:
Hypervolume approximation using achievement scalarizing functions for evolutionary many-objective optimization. IEEE Congress on Evolutionary Computation 2009: 530-537 - [c158]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Effects of using two neighborhood structures on the performance of cellular evolutionary algorithms for many-objective optimization. IEEE Congress on Evolutionary Computation 2009: 2508-2515 - [c157]Yusuke Nojima, Hisao Ishibuchi:
Interactive genetic fuzzy rule selection through evolutionary multiobjective optimization with user preference. MCDM 2009: 141-148 - [c156]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Adaptation of Scalarizing Functions in MOEA/D: An Adaptive Scalarizing Function-Based Multiobjective Evolutionary Algorithm. EMO 2009: 438-452 - [c155]Hisao Ishibuchi, Yusuke Nojima:
Discussions on Interpretability of Fuzzy Systems using Simple Examples. IFSA/EUSFLAT Conf. 2009: 1649-1654 - [c154]Yusuke Nojima, Hisao Ishibuchi:
Interactive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference. IFSA/EUSFLAT Conf. 2009: 1839-1844 - [c153]Hisao Ishibuchi, Hiroyuki Ohyanagi, Yusuke Nojima:
Evolution of cooperative behavior in a spatial iterated prisoner's dilemma game with different representation schemes of game strategies. FUZZ-IEEE 2009: 1568-1573 - [c152]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Selecting a small number of representative non-dominated solutions by a hypervolume-based solution selection approach. FUZZ-IEEE 2009: 1609-1614 - [c151]Rafael Alcalá, Yusuke Nojima, Francisco Herrera, Hisao Ishibuchi:
Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection. FUZZ-IEEE 2009: 1718-1723 - [c150]Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima:
Search ability of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. FUZZ-IEEE 2009: 1724-1729 - [c149]Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima:
Complexity, interpretability and explanation capability of fuzzy rule-based classifiers. FUZZ-IEEE 2009: 1730-1735 - [c148]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Single-objective and multi-objective formulations of solution selection for hypervolume maximization. GECCO 2009: 1831-1832 - [c147]Yusuke Nojima, Hisao Ishibuchi:
Effects of Data Reduction on the Generalization Ability of Parallel Distributed Genetic Fuzzy Rule Selection. ISDA 2009: 96-101 - [c146]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
Evolutionary Many-Objective Optimization by NSGA-II and MOEA/D with Large Populations. SMC 2009: 1758-1763 - [c145]Yusuke Nojima, Yusuke Nakashima, Hisao Ishibuchi:
Effects of the Use of Multiple Fuzzy Partitions on the Search Ability of Multiobjective Fuzzy Genetics-Based Machine Learning. SoCPaR 2009: 341-346 - [c144]Yuki Tsujimoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima, Hisao Ishibuchi:
Effects of Including Single-Objective Optimal Solutions in an Initial Population on Evolutionary Multiobjective Optimization. SoCPaR 2009: 352-357 - [c143]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Empirical Analysis of Using Weighted Sum Fitness Functions in NSGA-II for Many-Objective 0/1 Knapsack Problems. UKSim 2009: 71-76 - [p13]Gerald Schaefer, Tomoharu Nakashima, Hisao Ishibuchi:
Gene Expression Analysis by Fuzzy and Hybrid Fuzzy Classification. Fuzzy Systems in Bioinformatics and Computational Biology 2009: 127-140 - [i2]Matthias Ehrgott, Jussi Hakanen, Hisao Ishibuchi, Andreas Löhne, Mariano Luque, Kaisa Miettinen, Wlodzimierz Ogryczak, Olexandr Romanko, Theodor J. Stewart, Andrzej P. Wierzbicki:
09041 Working Group 4: MCDM and RIMO. Hybrid and Robust Approaches to Multiobjective Optimization 2009 - 2008
- [j42]Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer:
A cost-based fuzzy system for pattern classification with class importance. Artif. Life Robotics 12(1-2): 43-46 (2008) - [j41]Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi:
Effects of constructing fuzzy discretization from crisp discretization for rule-based classifiers. Artif. Life Robotics 13(1): 294-297 (2008) - [j40]Isao Kuwajima, Yusuke Nojima, Hisao Ishibuchi:
Obtaining accurate classifiers with Pareto-optimal and near Pareto-optimal rules. Artif. Life Robotics 13(1): 315-319 (2008) - [j39]Hisao Ishibuchi, Kaname Narukawa, Noritaka Tsukamoto, Yusuke Nojima:
An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization. Eur. J. Oper. Res. 188(1): 57-75 (2008) - [c142]Hisao Ishibuchi, Yusuke Nojima:
Evolutionary Multiobjective Fuzzy System Design. BIONETICS 2008: 30 - [c141]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Evolutionary many-objective optimization: A short review. IEEE Congress on Evolutionary Computation 2008: 2419-2426 - [c140]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nojima:
Scalability of multiobjective genetic local search to many-objective problems: Knapsack problem case studies. IEEE Congress on Evolutionary Computation 2008: 3586-3593 - [c139]Seiya Fujii, Tomoharu Nakashima, Hisao Ishibuchi:
A study on constructing fuzzy systems for high-level decision making in a car racing game. IEEE Congress on Evolutionary Computation 2008: 3626-3633 - [c138]El-Ghazali Talbi, Sanaz Mostaghim, Tatsuya Okabe, Hisao Ishibuchi, Günter Rudolph, Carlos A. Coello Coello:
Parallel Approaches for Multiobjective Optimization. Multiobjective Optimization 2008: 349-372 - [c137]Isao Kuwajima, Hisao Ishibuchi, Yusuke Nojima:
Effectiveness of designing fuzzy rule-based classifiers from Pareto-optimal rules. FUZZ-IEEE 2008: 1185-1192 - [c136]Seiya Fujii, Tomoharu Nakashima, Hisao Ishibuchi:
A study on constructing fuzzy systems for high-level decision making in a car racing game. FUZZ-IEEE 2008: 2299-2306 - [c135]Hisao Ishibuchi, Noritaka Tsukamoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima:
Effectiveness of scalability improvement attempts on the performance of NSGA-II for many-objective problems. GECCO 2008: 649-656 - [c134]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Maintaining the diversity of solutions by non-geometric binary crossover: a worst one-max solver competition case study. GECCO 2008: 1111-1112 - [c133]Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima:
Designing fuzzy rule-based classifiers that can visually explain their classification results to human users. GEFS 2008: 5-10 - [c132]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Evolutionary many-objective optimization. GEFS 2008: 47-52 - [c131]Yusuke Nojima, Hisao Ishibuchi:
Effects of Diversity Measures on the Design of Ensemble Classifiers by Multiobjective Genetic Fuzzy Rule Selection with a Multi-classifier Coding Scheme. HAIS 2008: 755-763 - [c130]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Examining the Effect of Elitism in Cellular Genetic Algorithms Using Two Neighborhood Structures. PPSN 2008: 458-467 - [c129]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima:
Use of Heuristic Local Search for Single-Objective Optimization in Multiobjective Memetic Algorithms. PPSN 2008: 743-752 - [c128]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Use of Local Ranking in Cellular Genetic Algorithms with Two Neighborhood Structures. SEAL 2008: 309-318 - [c127]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Behavior of Evolutionary Many-Objective Optimization. UKSim 2008: 266-271 - [c126]Hisao Ishibuchi:
Evolutionary multiobjective optimization and multiobjective fuzzy system design. CSTST 2008: 3-4 - [p12]Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima:
Multiobjective Classification Rule Mining. Multiobjective Problem Solving from Nature 2008: 219-240 - [p11]Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima:
Evolutionary Multi-objective Rule Selection for Classification Rule Mining. Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases 2008: 47-70 - [p10]Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima:
Evolutionary Multiobjective Design of Fuzzy Rule-Based Classifiers. Computational Intelligence: A Compendium 2008: 641-685 - [p9]Hisao Ishibuchi, Yusuke Nojima:
Pattern Classification with Linguistic Rules. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models 2008: 377-395 - 2007
- [j38]Tomoharu Nakashima, Yasuyuki Yokota, Yukio Shoji, Hisao Ishibuchi:
A genetic approach to the design of autonomous agents for futures trading. Artif. Life Robotics 11(2): 145-148 (2007) - [j37]Tomoharu Nakashima, Gerald Schaefer, Yasuyuki Yokota, Hisao Ishibuchi:
A weighted fuzzy classifier and its application to image processing tasks. Fuzzy Sets Syst. 158(3): 284-294 (2007) - [j36]Hisao Ishibuchi, Yusuke Nojima:
Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning. Int. J. Approx. Reason. 44(1): 4-31 (2007) - [j35]Yusuke Nojima, Hisao Ishibuchi:
Genetic rule selection with a multi-classifier coding scheme for ensemble classifier design. Int. J. Hybrid Intell. Syst. 4(3): 157-169 (2007) - [j34]Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer, Ales Drastich, Michal Zavisek:
Constructing Cost-Sensitive Fuzzy-Rule-Based Systems for Pattern Classification Problems. J. Adv. Comput. Intell. Intell. Informatics 11(6): 546-553 (2007) - [j33]Yew-Soon Ong, Natalio Krasnogor, Hisao Ishibuchi:
Special Issue on Memetic Algorithms. IEEE Trans. Syst. Man Cybern. Part B 37(1): 2-5 (2007) - [c125]Tomoharu Nakashima, Hisao Ishibuchi:
Mimicking Dribble Trajectories by Neural Networks for RoboCup Soccer Simulation. ISIC 2007: 658-663 - [c124]Ken Ohara, Yusuke Nojima, Hisao Ishibuchi:
A Study on Traffic Information Sharing Through Inter-Vehicle Communication. ISIC 2007: 670-675 - [c123]Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Yusuke Nojima:
An empirical study on the specification of the local search application probability in multiobjective memetic algorithms. IEEE Congress on Evolutionary Computation 2007: 2788-2795 - [c122]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Iterative approach to indicator-based multiobjective optimization. IEEE Congress on Evolutionary Computation 2007: 3967-3974 - [c121]Ken Ohara, Yusuke Nojima, Yumeka Kitano, Hisao Ishibuchi:
Effects of spatial structures on evolution of iterated prisoner's dilemma game strategies with probabilistic decision making. IEEE Congress on Evolutionary Computation 2007: 4051-4058 - [c120]Gerald Schaefer, Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi:
Cost-Sensitive Fuzzy Classification for Medical Diagnosis. CIBCB 2007: 312-316 - [c119]Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima:
Relation between Pareto-Optimal Fuzzy Rules and Pareto-Optimal Fuzzy Rule Sets. MCDM 2007: 42-49 - [c118]Hisao Ishibuchi, Yusuke Nojima:
Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization. EMO 2007: 51-65 - [c117]Hisao Ishibuchi:
Evolutionary Multiobjective Design of Fuzzy Rule-Based Systems. FOCI 2007: 9-16 - [c116]Hisao Ishibuchi:
Multiobjective Genetic Fuzzy Systems: Review and Future Research Directions. FUZZ-IEEE 2007: 1-6 - [c115]Tomoharu Nakashima, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi:
Introducing Class-Based Classification Priority in Fuzzy Rule-Based Classification Systems. FUZZ-IEEE 2007: 1-6 - [c114]Yusuke Nojima, Isao Kuwajima, Hisao Ishibuchi:
Data Set Subdivision for Parallel Distributed Implementation of Genetic Fuzzy Rule Selection. FUZZ-IEEE 2007: 1-6 - [c113]Gerald Schaefer, Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi:
Fuzzy Classification of Gene Expression Data. FUZZ-IEEE 2007: 1-6 - [c112]Gerald Schaefer, Tomoharu Nakashima, Michal Zavisek, Yasuyuki Yokota, Ales Drastich, Hisao Ishibuchi:
Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms. FUZZ-IEEE 2007: 1-5 - [c111]Hisao Ishibuchi, Yusuke Nojima, Noritaka Tsukamoto, Ken Ohara:
Effects of the use of non-geometric binary crossover on evolutionary multiobjective optimization. GECCO 2007: 829-836 - [c110]Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima:
Prescreening of Candidate Rules Using Association Rule Mining and Pareto-optimality in Genetic Rule Selection. KES (2) 2007: 509-516 - [c109]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Choosing extreme parents for diversity improvement in evolutionary multiobjective optimization algorithms. SMC 2007: 1946-1951 - [p8]Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima:
Use of Pareto-Optimal and Near Pareto-Optimal Candidate Rules in Genetic Fuzzy Rule Selection. Analysis and Design of Intelligent Systems using Soft Computing Techniques 2007: 387-396 - 2006
- [j32]Hisao Ishibuchi, Yusuke Nojima:
Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers. Int. J. Hybrid Intell. Syst. 3(3): 129-145 (2006) - [j31]Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
An approach to fuzzy default reasoning for function approximation. Soft Comput. 10(9): 850-864 (2006) - [c108]Hisao Ishibuchi, Naoki Namikawa, Ken Ohara:
Effects of Spatial Structures on Evolution of Iterated Prisoner's Dilemma Game Strategies in Single-Dimensional and Two-Dimensional Grids. IEEE Congress on Evolutionary Computation 2006: 976-983 - [c107]Hisao Ishibuchi, Yusuke Nojima, Tsutomu Doi:
Comparison between Single-Objective and Multi-Objective Genetic Algorithms: Performance Comparison and Performance Measures. IEEE Congress on Evolutionary Computation 2006: 1143-1150 - [c106]Tomoharu Nakashima, Masahiro Takatani, Naoki Namikawa, Hisao Ishibuchi, Manabu Nii:
Robust Evaluation of RoboCup Soccer Strategies by Using Match History. IEEE Congress on Evolutionary Computation 2006: 1195-1201 - [c105]Tomoharu Nakashima, Hisao Ishibuchi, Masahiro Takatani, Manabu Nii:
The Effect of Using Match History on the Evolution of RoboCup Soccer Team Strategies. CIG 2006: 60-66 - [c104]Tomoharu Nakashima, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi:
A Cost-based Fuzzy Rule-based System for Pattern Classification Problems. FUZZ-IEEE 2006: 251-255 - [c103]Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima:
Fuzzy Data Mining by Heuristic Rule Extraction and Multiobjective Genetic Rule Selection. FUZZ-IEEE 2006: 1633-1640 - [c102]Hisao Ishibuchi, Yusuke Nojima, Kaname Narukawa, Tsutomu Doi:
Incorporation of decision maker's preference into evolutionary multiobjective optimization algorithms. GECCO 2006: 741-742 - [c101]Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima:
Multiobjective genetic rule selection as a data mining postprocessing procedure. GECCO 2006: 1591-1592 - [c100]Yusuke Nojima, Hisao Ishibuchi:
Designing Fuzzy Ensemble Classifiers by Evolutionary Multiobjective Optimization with an Entropy-Based Diversity Criterion. HIS 2006: 59 - [c99]Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima:
Finding Simple Fuzzy Classification Systems with High Interpretability Through Multiobjective Rule Selection. KES (2) 2006: 86-93 - [c98]Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima:
Incorporation of Scalarizing Fitness Functions into Evolutionary Multiobjective Optimization Algorithms. PPSN 2006: 493-502 - [c97]Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima:
Effects of Using Two Neighborhood Structures in Cellular Genetic Algorithms for Function Optimization. PPSN 2006: 949-958 - [c96]Tomoharu Nakashima, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi:
Examining the Effect of Cost Assignment on the Performance of Cost-Based Classification Systems. SMC 2006: 2772-2777 - [p7]Hisao Ishibuchi, Yusuke Nojima:
Fuzzy Ensemble Design through Multi-Objective Fuzzy Rule Selection. Multi-Objective Machine Learning 2006: 507-530 - 2005
- [b1]Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii:
Classification and modeling with linguistic information granules - advanced approaches to linguistic data mining. Advanced information processing, Springer 2005, ISBN 978-3-540-20767-2, pp. I-XI, 1-307 - [j30]Hisao Ishibuchi, Naoki Namikawa:
Evolution of iterated prisoner's dilemma game strategies in structured demes under random pairing in game playing. IEEE Trans. Evol. Comput. 9(6): 552-561 (2005) - [j29]Hisao Ishibuchi, Takashi Yamamoto:
Rule Weight Specification in Fuzzy Rule-Based Classification Systems. IEEE Trans. Fuzzy Syst. 13(4): 428-435 (2005) - [j28]Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
Hybridization of fuzzy GBML approaches for pattern classification problems. IEEE Trans. Syst. Man Cybern. Part B 35(2): 359-365 (2005) - [c95]Satoshi Yokoyama, Naoki Namikawa, Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Developing a Goal Keeper for Simulated RoboCup Soccer and its Performance Evaluation. AMiRE 2005: 75-80 - [c94]Hisao Ishibuchi, Naoki Namikawa:
Evolution of cooperative behavior in the iterated prisoner's dilemma under random pairing in game playing. Congress on Evolutionary Computation 2005: 2637-2644 - [c93]Hisao Ishibuchi, Kaname Narukawa:
Recombination of Similar Parents in EMO Algorithms. EMO 2005: 265-279 - [c92]Yusuke Nojima, Kaname Narukawa, Shiori Kaige, Hisao Ishibuchi:
Effects of Removing Overlapping Solutions on the Performance of the NSGA-II Algorithm. EMO 2005: 341-354 - [c91]Hisao Ishibuchi, Shiori Kaige, Kaname Narukawa:
Comparison Between Lamarckian and Baldwinian Repair on Multiobjective 0/1 Knapsack Problems. EMO 2005: 370-385 - [c90]Hisao Ishibuchi, Yusuke Nojima:
Multiobjective Formulations of Fuzzy Rule-Based Classification System Design. EUSFLAT Conf. 2005: 285-290 - [c89]Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer:
Learning Fuzzy If-Then Rules for Pattern Classi cation with Weighted Training Patterns. EUSFLAT Conf. 2005: 1064-1069 - [c88]Hisao Ishibuchi, Yusuke Nojima:
Comparison between Fuzzy and Interval Partitions in Evolutionary Multiobjective Design of Rule-Based Classification Systems. FUZZ-IEEE 2005: 430-435 - [c87]Kaname Narukawa, Yusuke Nojima, Hisao Ishibuchi:
Modification of Evolutionary Multiobjective Optimization Algorithms for Multiobjective Design of Fuzzy Rule-Based Classification Systems. FUZZ-IEEE 2005: 809-814 - [c86]Hisao Ishibuchi, Kaname Narukawa:
Comparison of evolutionary multiobjective optimization with rference solution-based single-objective approach. GECCO 2005: 787-794 - [c85]Hisao Ishibuchi, Kaname Narukawa, Yusuke Nojima:
An empirical study on the handling of overlapping solutions in evolutionary multiobjective optimization. GECCO 2005: 817-824 - [c84]Hisao Ishibuchi, Kaname Narukawa:
Spatial Implementation of Evolutionary Multiobjective Algorithms with Partial Lamarckian Repair for Multiobjective Knapsack Problems. HIS 2005: 265-270 - [c83]Hisao Ishibuchi, Yusuke Nojima:
Performance Evaluation of Evolutionary Multiobjective Approaches to the Design of Fuzzy Rule-Based Ensemble Classifiers. HIS 2005: 271-276 - [c82]Tomoharu Nakashima, Masahiro Takatani, Masayo Udo, Hisao Ishibuchi, Manabu Nii:
Performance Evaluation of an Evolutionary Method for RoboCup Soccer Strategies. RoboCup 2005: 616-623 - [c81]Hiroko Kitano, Tomoharu Nakashima, Hisao Ishibuchi:
Behavior Analysis of Futures Trading Agents Using Fuzzy Rule Extraction. SMC 2005: 1477-1481 - [p6]Tomoharu Nakashima, Hisao Ishibuchi:
Using Boosting Techniques to Improve the Performance of Fuzzy Classification Systems. Classification and Clustering for Knowledge Discovery 2005: 147-157 - [p5]Tomoharu Nakashima, Takanobu Ariyama, Hiroko Kitano, Hisao Ishibuchi:
A Fuzzy Rule-Based Trading Agent: Analysis and Knowledge Extraction. Computational Intelligence for Modelling and Prediction 2005: 265-277 - [i1]Hisao Ishibuchi:
Effects of Crossover Operations on the Performance of EMO Algorithms. Practical Approaches to Multi-Objective Optimization 2005 - 2004
- [j27]Hisao Ishibuchi, Takashi Yamamoto:
Comparison of Heuristic Criteria for Fuzzy Rule Selection in Classification Problems. Fuzzy Optim. Decis. Mak. 3(2): 119-139 (2004) - [j26]Hisao Ishibuchi, Takashi Yamamoto:
Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. Fuzzy Sets Syst. 141(1): 59-88 (2004) - [j25]Hisao Ishibuchi:
Book Review: "Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases" by Oscar Cordon, Francisco Herrera, Frank Hoffmann and Luis Magdalena; World Scientific, Singapore, New Jersey, London, Hong Kong, 2001, 462pp., ISBN 981-02-4016-3. Fuzzy Sets Syst. 141(1): 161-162 (2004) - [j24]Hisao Ishibuchi, Shiori Kaige:
Implementation of Simple Multiobjective Memetic Algorithms and Its Applications to Knapsack Problems. Int. J. Hybrid Intell. Syst. 1(1): 22-35 (2004) - [c80]Hisao Ishibuchi, Kiyoshi Narukawa:
Performance evaluation of simple multiobjective genetic local search algorithms on multiobjective 0/1 knapsack problems. IEEE Congress on Evolutionary Computation 2004: 441-448 - [c79]Hisao Ishibuchi, Takashi Yamamoto:
Heuristic extraction of fuzzy classification rules using data mining techniques: an empirical study on benchmark data sets. FUZZ-IEEE 2004: 161-166 - [c78]Hisao Ishibuchi, Kaname Narukawa:
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization. GECCO (1) 2004: 1246-1258 - [c77]Hisao Ishibuchi, Youhei Shibata:
Mating Scheme for Controlling the Diversity-Convergence Balance for Multiobjective Optimization. GECCO (1) 2004: 1259-1271 - [c76]Hisao Ishibuchi, Kaname Narukawa:
Comparison of Local Search Implementation Schemes in Hybrid Evolutionary Multiobjective Optimization Algorithms. HIS 2004: 404-409 - [c75]Tomoharu Nakashima, Hisao Ishibuchi, Andrzej Bargiela:
A Study on Weighting Training Patterns for Fuzzy Rule-Based Classification Systems. MDAI 2004: 60-69 - [c74]Hisao Ishibuchi, Satoshi Namba:
Evolutionary Multiobjective Knowledge Extraction for High-Dimensional Pattern Classification Problems. PPSN 2004: 1123-1132 - [c73]Tomoharu Nakashima, Masahiro Takatani, Masayo Udo, Hisao Ishibuchi:
An evolutionary approach for strategy learning in RoboCup soccer. SMC (2) 2004: 2023-2028 - [c72]Tomoharu Nakashima, Hiroko Kitano, Hisao Ishibuchi:
Development of a fuzzy position controller for an autonomously trading agent. SMC (3) 2004: 2338-2343 - [c71]Hisao Ishibuchi, Takashi Yamamoto:
Multi-objective evolutionary design of fuzzy rule-based systems. SMC (3) 2004: 2362-2367 - [c70]Tomoharu Nakashima, Hisao Ishibuchi, Andrzej Bargiela:
Constructing fuzzy classification systems from weighted training patterns. SMC (3) 2004: 2386-2391 - 2003
- [j23]Hisao Ishibuchi, Ryoji Sakamoto, Tomoharu Nakashima:
Learning fuzzy rules from iterative execution of games. Fuzzy Sets Syst. 135(2): 213-240 (2003) - [j22]Hisao Ishibuchi, Tadashi Yoshida, Tadahiko Murata:
Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Trans. Evol. Comput. 7(2): 204-223 (2003) - [c69]Hisao Ishibuchi, Shiori Kaige:
Effects of repair procedures on the performance of EMO algorithms for multiobjective 0/1 knapsack problems. IEEE Congress on Evolutionary Computation 2003: 2254-2261 - [c68]Tomoharu Nakashima, Takanobu Ariyama, Takanori Yoshida, Hisao Ishibuchi:
Performance evaluation of combined cellular genetic algorithms for function optimization problems. CIRA 2003: 295-299 - [c67]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
Credit assignment by fuzzy rule-based systems in fuzzy classifier ensembles. CIRA 2003: 664-669 - [c66]Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Acquiring the positioning skill in a soccer game using a fuzzy Q-learning. CIRA 2003: 1488-1491 - [c65]Hisao Ishibuchi, Youhei Shibata:
An Empirical Study on the Effect of Mating Restriction on the Search Ability of EMO Algorithms. EMO 2003: 433-447 - [c64]Tadahiko Murata, Hiroyuki Nozawa, Hisao Ishibuchi, Mitsuo Gen:
Modification of Local Search Directions for Non-dominated Solutions in CellularMultiobjective Genetic Algorithms forPattern Classification Problems. EMO 2003: 593-607 - [c63]Hisao Ishibuchi, Takashi Yamamoto:
Effects of Three-Objective Genetic Rule Selection on the Generalization Ability of Fuzzy Rule-Based Systems. EMO 2003: 608-622 - [c62]Takashi Yamamoto, Hisao Ishibuchi:
Performance evaluation of three-objective genetic rule selection. FUZZ-IEEE 2003: 149-154 - [c61]Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Implementation of fuzzy Q-learning for a soccer agent. FUZZ-IEEE 2003: 533-536 - [c60]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
A boosting algorithm with subset selection of training patterns. FUZZ-IEEE 2003: 690-695 - [c59]Tomoharu Nakashima, Takanobu Ariyama, Hisao Ishibuchi:
Extracting linguistic knowledge and its use as decision support in a virtual futures market. FUZZ-IEEE 2003: 708-713 - [c58]Hisao Ishibuchi, Takashi Yamamoto:
Deriving fuzzy discretization from interval discretization. FUZZ-IEEE 2003: 749-754 - [c57]Hisao Ishibuchi, Youhei Shibata:
A Similarity-Based Mating Scheme for Evolutionary Multiobjective Optimization. GECCO 2003: 1065-1076 - [c56]Hisao Ishibuchi, Takashi Yamamoto:
Evolutionary Multiobjective Optimization for Generating an Ensemble of Fuzzy Rule-Based Classifiers. GECCO 2003: 1077-1088 - [c55]Tadahiko Murata, Shiori Kaige, Hisao Ishibuchi:
Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms. GECCO 2003: 1234-1245 - [c54]Hisao Ishibuchi, Shiori Kaige:
A Simple but Powerful Multiobjective Hybrid Genetic Algorithm. HIS 2003: 244-251 - [c53]Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
A Fuzzy Reinforcement Learning for a Ball Interception Problem. RoboCup 2003: 559-567 - [c52]Shiori Kaige, Tadahiko Murata, Hisao Ishibuchi:
Performance evaluation of memetic EMO algorithms using dominance relation-based replacement rules on MOO test problems. SMC 2003: 14-19 - [c51]Tomoham Nakashima, Gaku Nakai, Hisao Ishibuchi:
Constructing fuzzy ensembles for pattern classification problems. SMC 2003: 3200-3205 - [c50]Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Knowledge acquisition for a soccer agent by fuzzy reinforcement learning. SMC 2003: 4256-4261 - [p4]Hisao Ishibuchi, Takashi Yamamoto:
Interpretability Issues in Fuzzy Genetics-Based Machine Learning for Linguistic Modelling. Modelling with Words 2003: 209-228 - 2002
- [c49]Tadahiko Murata, Hiroyuki Nozawa, Yasuhiro Tsujimura, Mitsuo Gen, Hisao Ishibuchi:
Effect of local search on the performance of cellular multiobjective genetic algorithms for designing fuzzy rule-based classification systems. IEEE Congress on Evolutionary Computation 2002: 663-668 - [c48]Hisao Ishibuchi, Tadsahi Yoshida, Tadahiko Murata:
Selection of initial solutions for local search in multiobjective genetic local search. IEEE Congress on Evolutionary Computation 2002: 950-955 - [c47]Tomoharu Nakashima, Takanobu Ariyama, Hisao Ishibuchi:
On-Line Learning of a Fuzzy System for a Future Market. FSKD 2002: 54-58 - [c46]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
A Boosting Algorithm of Fuzzy Rule-Based Systems for Pattern Classification Problems. FSKD 2002: 155-158 - [c45]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
Improving the performance of fuzzy classification systems by membership function learning and feature selection. FUZZ-IEEE 2002: 488-493 - [c44]Hisao Ishibuchi, Takashi Yamamoto:
Comparison of heuristic rule weight specification methods. FUZZ-IEEE 2002: 908-913 - [c43]Hisao Ishibuchi, Teppei Seguchi:
Successive adaptation of fuzzy rule-based systems in a multi-agent model. FUZZ-IEEE 2002: 1009-1014 - [c42]Hisao Ishibuchi, Takashi Yamamoto:
Performance evaluation of fuzzy partitions with different fuzzification grades. FUZZ-IEEE 2002: 1198-1203 - [c41]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
A fuzzy rule-based system for ensembling classification systems. FUZZ-IEEE 2002: 1432-1437 - [c40]Hisao Ishibuchi, Takashi Yamamoto:
Fuzzy Rule Selection By Data Mining Criteria And Genetic Algorithms. GECCO 2002: 399-406 - [c39]Hisao Ishibuchi, Tadashi Yoshida, Tadahiko Murata:
Balance Between Genetic Search And Local Search In Hybrid Evolutionary Multi-criterion Optimization Algorithms. GECCO 2002: 1301-1308 - [c38]Hisao Ishibuchi, Takashi Yamamoto:
Comparison of Fuzzy Rule Selection Criteria for Classification Problems. HIS 2002: 132-141 - [c37]Hisao Ishibuchi, Tadashi Yoshida:
Hybrid Evolutionary Multi-Objective Optimization Algorithms. HIS 2002: 163-172 - 2001
- [j21]Hisao Ishibuchi, Manabu Nii:
Fuzzy regression using asymmetric fuzzy coefficients and fuzzified neural networks. Fuzzy Sets Syst. 119(2): 273-290 (2001) - [j20]Hisao Ishibuchi, Manabu Nii:
Numerical analysis of the learning of fuzzified neural networks from fuzzy if-then rules. Fuzzy Sets Syst. 120(2): 281-307 (2001) - [j19]Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata:
Three-objective genetics-based machine learning for linguistic rule extraction. Inf. Sci. 136(1-4): 109-133 (2001) - [j18]Hisao Ishibuchi, Tomoharu Nakashima, Ryoji Sakamoto:
Evolution of unplanned coordination in a market selection game. IEEE Trans. Evol. Comput. 5(5): 524-534 (2001) - [j17]Hisao Ishibuchi, Tomoharu Nakashima:
Effect of rule weights in fuzzy rule-based classification systems. IEEE Trans. Fuzzy Syst. 9(4): 506-515 (2001) - [c36]Hisao Ishibuchi, Tomoharu Nakaskima:
Three-objective optimization in linguistic function approximation. CEC 2001: 340-347 - [c35]Hisao Ishibuchi, Ryoji Sakamoto, Tomoharu Nakashima:
Effect of localized selection on the evolution of unplanned coordination in a market selection game. CEC 2001: 1011-1018 - [c34]Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen:
Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms. EMO 2001: 82-95 - [c33]Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata:
Multiobjective Optimization in Linguistic Rule Extraction from Numerical Data. EMO 2001: 588-602 - [c32]Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
Linguistic Modelling for Function Approximation Using Grid Partitions. FUZZ-IEEE 2001: 47-50 - [c31]Hisao Ishibuchi, Ryoji Sakamoto, Tomoharu Nakashima:
Adaption of Fuzzy Rule-Based Systems for Game Playing . FUZZ-IEEE 2001: 1448-1451 - [c30]Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
Determination of Rule Weights of Fuzzy Association Rules. FUZZ-IEEE 2001: 1555-1558 - [c29]Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
Fuzzy Data Mining: Effect of Fuzzy Discretization. ICDM 2001: 241-248 - 2000
- [j16]Hisao Ishibuchi, Manabu Nii:
Neural networks for soft decision making. Fuzzy Sets Syst. 115(1): 121-140 (2000) - [j15]Hisao Ishibuchi, Tomoharu Nakashima:
Pattern and Feature Selection by Genetic Algorithms in Nearest Neighbor Classification. J. Adv. Comput. Intell. Intell. Informatics 4(2): 138-145 (2000) - [c28]Hisao Ishibuchi, Tomoharu Nakashima:
Effect of rule weights in fuzzy rule-based classification systems. FUZZ-IEEE 2000: 59-64 - [c27]Hisao Ishibuchi, Tomoharu Nakashima, Tetsuya Kuroda:
A hybrid fuzzy GBML algorithm for designing compact fuzzy rule-based classification systems. FUZZ-IEEE 2000: 706-711 - [c26]Hisao Ishibuchi, Tomoharu Nakashima:
Linguistic Rule Extraction by Genetics-Based Machine Learning. GECCO 2000: 195-202 - [c25]Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen:
Cellular Genetic Local Search for Multi-Objective Optimization. GECCO 2000: 307-314 - [c24]Hisao Ishibuchi, Tatsuo Nakari, Tomoharu Nakashima:
Evolution of Strategies in Spatial IPD Games with Structure Demes. GECCO 2000: 817-824 - [c23]Hisao Ishibuchi, Tomoharu Nakashima:
Multi-objective pattern and feature selection by a genetic algorithm. GECCO 2000: 1069-
1990 – 1999
- 1999
- [j14]Hisao Ishibuchi, Tomoharu Nakashima, Takehiko Morisawa:
Voting in fuzzy rule-based systems for pattern classification problems. Fuzzy Sets Syst. 103(2): 223-238 (1999) - [j13]Hisao Ishibuchi, Tadahiko Murata, Tomoharu Nakashima:
Linguistic Rule Extraction from Numerical Data for High-dimensional Classification Problems. J. Adv. Comput. Intell. Intell. Informatics 3(5): 386-393 (1999) - [j12]Hisao Ishibuchi, Tomoharu Nakaskima:
Improving the performance of fuzzy classifier systems for pattern classification problems with continuous attributes. IEEE Trans. Ind. Electron. 46(6): 1057-1068 (1999) - [j11]Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata:
Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems. IEEE Trans. Syst. Man Cybern. Part B 29(5): 601-618 (1999) - [c22]Hisao Ishibuchi, Tatsuo Nakari, Tomoham Nakashima:
Evolution of neighborly relations in a spatial IPD game with cooperative players and hostile players. CEC 1999: 929-936 - [c21]Hisao Ishibuchi, Tomoharu Nakashima:
Designing compact fuzzy rule-based systems with default hierarchies for linguistic approximation. CEC 1999: 2341-2348 - [c20]Hisao Ishibuchi, Manabu Nii, Kimiko Tanaka:
Decreasing excess fuzziness in fuzzy outputs from neural networks for linguistic rule extraction. IJCNN 1999: 4217-4222 - 1998
- [j10]Hisao Ishibuchi, Tadahiko Murata:
A multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Trans. Syst. Man Cybern. Part C 28(3): 392-403 (1998) - [c19]Tadahiko Murata, Hisao Ishibuchi, Tomoharu Nakashima, Mitsuo Gen:
Fuzzy Partition and Input Selection by Genetic Algorithms for Designing Fuzzy Rule-Based Classification Systems. Evolutionary Programming 1998: 407-416 - [c18]Hisao Ishibuchi, Tomoharu Nakashima:
A study on generating fuzzy classification rules using histograms. KES (1) 1998: 132-140 - [c17]Hisao Ishibuchi, Manabu Nii:
Improving the generalization ability of neural networks by interval arithmetic. KES (1) 1998: 231-236 - [c16]Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen:
Neighborhood structures for genetic local search algorithms. KES (2) 1998: 259-263 - [c15]Manabu Nii, Hisao Ishibuchi:
Fuzzy arithmetic in neural networks for linguistic rule extraction. KES (2) 1998: 387-394 - [c14]Hisao Ishibuchi, Tomoharu Nakashima:
Evolution of Reference Sets in Nearest Neighbor Classification. SEAL 1998: 82-89 - [c13]Kimiko Tanaka, Manabu Nii, Hisao Ishibuchi:
Learning from Linguistic Rules and Rule Extraction for Function Approximation by Neural Networks. SEAL 1998: 317-324 - [p3]Hisao Ishibuchi, Manabu Nii:
Fuzzy neural networks techniques and their applications. Fuzzy logic and expert systems applications 1998: 1-56 - 1997
- [j9]Ken Nozaki, Hisao Ishibuchi, Hideo Tanaka:
A simple but powerful heuristic method for generating fuzzy rules from numerical data. Fuzzy Sets Syst. 86(3): 251-270 (1997) - [j8]Hisao Ishibuchi, Tadahiko Murata, I. Burhan Türksen:
Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems. Fuzzy Sets Syst. 89(2): 135-150 (1997) - [c12]Hisao Ishibuchi, Tadahiko Murata, Shigemitsu Tomioka:
Effectiveness of Genetic Local Search Algorithms. ICGA 1997: 505-512 - [c11]Hisao Ishibuchi, Manabu Nii:
Possibilistic fuzzy classification using neural networks. ICNN 1997: 1433-1438 - [c10]Hisao Ishibuchi, Manabu Nii, Tadahiko Murata:
Linguistic rule extraction from neural networks and genetic-algorithm-based rule selection. ICNN 1997: 2390-2395 - 1996
- [j7]Ken Nozaki, Hisao Ishibuchi, Hideo Tanaka:
Adaptive fuzzy rule-based classification systems. IEEE Trans. Fuzzy Syst. 4(3): 238-250 (1996) - [c9]Hisao Ishibuchi, Tadahiko Murata:
Multi-Objective Genetic Local Search Algorithm. International Conference on Evolutionary Computation 1996: 119-124 - [c8]Tadahiko Murata, Hisao Ishibuchi:
Positive and Negative Combination Effects of Crossover and Mutation Operators in Sequencing Problems. International Conference on Evolutionary Computation 1996: 170-175 - [c7]Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata:
Genetic-Algorithm-Based Approaches to the Design of Fuzzy Systems for Multi-Dimensional Pattern Classification Problems. International Conference on Evolutionary Computation 1996: 229-234 - [c6]Hisao Ishibuchi, Manabu Nii:
Generating fuzzy if-then rules from trained neural networks: linguistic analysis of neural networks. ICNN 1996: 1133-1138 - [c5]Hisao Ishibuchi, Manabu Nii:
Fuzzy regression analysis by neural networks with non-symmetric fuzzy number weights. ICNN 1996: 1191-1196 - 1995
- [j6]Hisao Ishibuchi:
Preface: 3rd international conference on fuzzy logic, neural nets, and soft computing. Int. J. Approx. Reason. 13(4): 247-248 (1995) - [j5]Hisao Ishibuchi, Kouichi Morioka, I. Burhan Türksen:
Learning by fuzzified neural networks. Int. J. Approx. Reason. 13(4): 327-358 (1995) - [j4]Hisao Ishibuchi, Ken Nozaki, Naohisa Yamamoto, Hideo Tanaka:
Selecting fuzzy if-then rules for classification problems using genetic algorithms. IEEE Trans. Fuzzy Syst. 3(3): 260-270 (1995) - [c4]Hisao Ishibuchi, Kouichi Morioka:
Classification of fuzzy input patterns by neural networks. ICNN 1995: 3118-3123 - [c3]Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata:
A Fuzzy Classifier System That Generates Linguistic Rules for Pattern Classification Problems. IEEE/Nagoya-University World Wisepersons Workshop 1995: 35-54 - 1994
- [j3]Hisao Ishibuchi, Hideo Tanaka, Hidehiko Okada:
Interpolation of fuzzy if-then rules by neural networks. Int. J. Approx. Reason. 10(1): 3-27 (1994) - [c2]Tadahiko Murata, Hisao Ishibuchi:
Performance Evaluation of Genetic Algorithms for Flowshop Scheduling Problems. International Conference on Evolutionary Computation 1994: 812-817 - 1993
- [j2]Hideo Tanaka, Hisao Ishibuchi:
Evidence theory of exponential possibility distributions. Int. J. Approx. Reason. 8(2): 123-140 (1993) - [j1]Hisao Ishibuchi, Ryosuke Fujioka, Hideo Tanaka:
Neural networks that learn from fuzzy if-then rules. IEEE Trans. Fuzzy Syst. 1(2): 85-97 (1993) - [c1]Hisao Ishibuchi, Hideo Tanaka, Hidehiko Okada:
Fuzzy neural networks with fuzzy weights and fuzzy biases. ICNN 1993: 1650-1655 - [p2]Hisao Ishibuchi, S. Misaki, Hideo Tanaka:
Simulated annealing with modified generation mechanism for flow shop scheduling problems. Robotics, Mechatronics and Manufacturing Systems 1993: 809-814 - 1992
- [p1]Hideo Tanaka, Hisao Ishibuchi, Takeo Shigenaga:
Fuzzy Inference System Based on Rough Sets and Its Application to Medical Diagnosis. Intelligent Decision Support 1992: 111-117
Coauthor Index
[j180] [j174] [j171] [c364] [c363] [i35] [i34] [j160] [c345] [c343] [c341] [i31] [i29] [i28] [c318] [i23] [j129] [j128] [c315] [c311] [c309] [c306] [c305] [c302] [c300] [c291] [j121] [c288] [c285] [c284] [c282] [c281] [c275] [c271] [c270] [c269] [c268] [c266] [c262] [c261] [c260] [c259] [c258] [c257]
[p13] [j42] [c139] [c136] [j38] [j37] [j34] [c125] [c120] [c115] [c113] [c112] [j31] [c106] [c105] [c104] [c96] [b1] [j28] [c95] [c89] [c82] [c81] [p6] [p5] [c75] [c73] [c72] [c70] [j23] [c68] [c67] [c66] [c61] [c60] [c59] [c53] [c50] [c47] [c46] [c45] [c41] [j19] [j18] [j17] [c35] [c33] [c32] [c31] [c30] [c29] [j15] [c28] [c27] [c26] [c24] [c23] [j14] [j13] [j11] [c21] [c19] [c18] [c14] [c7] [c3]
[c390] [c389] [c387] [c386] [c385] [c383] [c382] [c379] [c372] [i38] [j172] [j170] [j167] [j165] [j162] [c370] [c368] [c367] [c366] [c365] [c361] [c360] [c358] [c355] [c354] [c353] [c352] [c351] [c349] [c348] [c347] [c346] [j155] [c340] [i33] [i26] [j144] [c334] [c326] [c322] [c319] [i22] [j139] [c301] [c292] [c277]
[j180] [j174] [j171] [c364] [c363] [i35] [i34] [j160] [j159] [j148] [c345] [c343] [c341] [i31] [i29] [i28] [j142] [j140] [c318] [i23] [j129] [j128] [j123] [c315] [c311] [c309] [c306] [c305] [c302] [c300] [c291] [j121] [c288] [c285] [c284] [c282] [c281] [c275] [c271] [c270] [j104] [j100] [j98] [c269] [c268] [c266] [c262] [c261] [c260] [c259] [c258] [c257] [j88] [c256] [c255] [c253] [c252] [c251] [c250] [c249] [c248] [j79] [c247] [c246] [c245] [c244] [c243] [c242] [c241] [c240] [c239] [c238] [c235] [c234] [c233] [c231] [j70] [c230] [c229] [c228] [c227] [c226] [c225] [c224] [c223] [c221] [c220] [c219] [c218] [c217] [p15] [j65] [c215] [c214] [c213] [c212] [c211] [c210] [c208] [c207] [c206] [c205] [c204] [j64] [j63] [j62] [j61] [c203] [c202] [c201] [c200] [c199] [c198] [c197] [c196] [c195] [c194] [c193] [c192] [c191] [c190] [j59] [c189] [c188] [c187] [c186] [c185] [c184] [c183] [c182] [j58] [j57] [j56] [j55] [j54] [j53] [c181] [c180] [c179] [c178] [c177] [c176] [c175] [c174] [c173] [c172] [j50] [c171] [c170] [c169] [c168] [c167] [c166] [c165] [c164] [c163] [c162] [c161] [c160] [j49] [j48] [j47] [j46] [j45] [j43] [c159] [c158] [c157] [c156] [c155] [c154] [c153] [c152] [c151] [c150] [c149] [c148] [c147] [c146] [c145] [c144] [c143] [j41] [j40] [j39] [c142] [c141] [c140] [c137] [c135] [c134] [c133] [c132] [c131] [c130] [c129] [c128] [c127] [p12] [p11] [p10] [p9] [j36] [j35] [c124] [c123] [c122] [c121] [c119] [c118] [c114] [c111] [c110] [c109] [p8] [j32] [c107] [c103] [c102] [c101] [c100] [c99] [c98] [c97] [p7] [c92] [c90] [c88] [c87] [c85] [c83]
[j176] [c389] [c388] [c384] [c383] [c382] [c381] [c374] [c372] [j172] [j168] [c368] [c367] [c361] [c359] [c354] [c353] [c352] [c348] [c346] [j157] [j149] [c344] [c342] [c338] [i33] [j147] [j141] [c336] [c335] [c332] [c331] [c324] [c322] [c320] [c317] [c316] [j138] [j137] [j136] [c307] [c297] [c296] [c295] [c294] [i17] [i15] [i14] [i5] [c276] [c272]
[j178] [j176] [c388] [c387] [c386] [c385] [c381] [c379] [c376] [i38] [j172] [j168] [j167] [j166] [j165] [j162] [c366] [c362] [c359] [c358] [c357] [c352] [c351] [c350] [c347] [j157] [j155] [j153] [j149] [c342] [c340] [c337] [i33] [i32] [i30] [i26] [j147] [c336] [c335] [c334] [c332] [c331] [c326] [c325] [c324] [c322] [c321] [c320] [c319] [c317] [i24] [i22] [i20] [j139] [j137] [j136] [j134] [j131] [j126] [j125] [c314] [c313] [c307] [c301] [c299] [c298] [c297] [c296] [c295] [c294] [c292] [c290] [i19] [i17] [i16] [i15] [i14] [i5] [c289] [c287] [c286] [c278] [c277] [c276] [c274] [c272] [c267] [c264] [c262] [c261]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-18 20:45 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
