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ORCIDYongchuan Tang
Yong-chuan Tang
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2020 – today
- 2024
[j69]Yan Li, Lingyun Sun, Yongchuan Tang:
DPC-DNG: Graph-based label propagation of k-nearest higher-density neighbors for density peaks clustering. Appl. Soft Comput. 161: 111773 (2024)- [j68]Wei Li, Yongxing He, Yongchuan Tang:
Improving mode exploring capability of generative adversarial nets by self-organizing map. Neurocomputing 576: 127244 (2024) - [j67]Yongchuan Tang
, Lei Wu, Yubo Huang, Deyun Zhou:
An improved approach for incomplete information modeling in the evidence theory and its application in classification. Soft Comput. 28(17-18): 10187-10200 (2024) - [c41]Teng Zhou, Yongchuan Tang:
TwinDiffusion: Enhancing Coherence and Efficiency in Panoramic Image Generation with Diffusion Models. ECAI 2024: 386-393 - [i5]Yongchuan Tang, Rongfei Li:
The negation of permutation mass function. CoRR abs/2403.06483 (2024) - [i4]Teng Zhou, Yongchuan Tang:
TwinDiffusion: Enhancing Coherence and Efficiency in Panoramic Image Generation with Diffusion Models. CoRR abs/2404.19475 (2024) - 2023
- [j66]Yongchuan Tang, Shuaihong Wu, Ying Zhou, Yubo Huang, Deyun Zhou:
A New Reliability Coefficient Using Betting Commitment Evidence Distance in Dempster-Shafer Evidence Theory for Uncertain Information Fusion. Entropy 25(3): 462 (2023) - [j65]Yongchuan Tang, Yonghao Zhou, Ying Zhou, Yubo Huang, Deyun Zhou:
Failure Mode and Effects Analysis on the Air System of an Aero Turbofan Engine Using the Gaussian Model and Evidence Theory. Entropy 25(5): 757 (2023) - [j64]Lei Wu, Yongchuan Tang, Liuyuan Zhang, Yubo Huang:
Uncertainty Management in Assessment of FMEA Expert Based on Negation Information and Belief Entropy. Entropy 25(5): 800 (2023) - [j63]Wei Li, Yongxing He, Xiaoyu Zhang, Yongchuan Tang:
Filter pruning via feature map clustering. Intell. Data Anal. 27(4): 911-933 (2023) - [j62]Huibin Shi, Zexi Hua, Jianyi Chen, Yongchuan Tang, Rujiang He:
Detection and recognition of digital instrument in substation using improved YOLO-v3. Signal Image Video Process. 17(6): 2971-2979 (2023) - [j61]Yiyi Liu, Yongchuan Tang, Zhengyi Yang, Deyun Zhou, Li Li, Shuning Wang:
Improved fuzzy evidential DEMATEL method based on two-dimensional correlation coefficient and negation evidence. Soft Comput. 27(16): 11177-11192 (2023) - [c40]Yongchuan Tang, Shiting Tan, Ying Zhou, Yubo Huang, Deyun Zhou:
BDWRPN: Belief divergence weighted risk priority number for failure modes ranking and its application. ECC 2023: 1-6 - [c39]Yongchuan Tang, Lei Wu, Yubo Huang, Deyun Zhou:
A new classification method using the generalized basic probability assignment. ECC 2023: 1-6 - [c38]Jiangjie Huang, Xiaoyu Zhang, Yongchuan Tang:
Research on Ideation Process and Design Productivity of ChatGPT Based on LASSO and Linkography. ISCID 2023: 184-187 - 2022
- [j60]Rongfei Li, Zhiyuan Chen, Hao Li, Yongchuan Tang:
A new distance-based total uncertainty measure in Dempster-Shafer evidence theory. Appl. Intell. 52(2): 1209-1237 (2022) - [j59]Yujie Chen, Zexi Hua, Yongchuan Tang, Baoxin Li:
Multi-Source Information Fusion Based on Negation of Reconstructed Basic Probability Assignment with Padded Gaussian Distribution and Belief Entropy. Entropy 24(8): 1164 (2022) - [j58]Yongchuan Tang, Yong Chen, Deyun Zhou:
Measuring Uncertainty in the Negation Evidence for Multi-Source Information Fusion. Entropy 24(11): 1596 (2022) - [j57]Pei Chen, Zejian Li, Yangkang Zhang, Yongchuan Tang, Lingyun Sun:
USIS: A unified semantic image synthesis model trained on a single or multiple samples. Neurocomputing 514: 70-82 (2022) - [j56]Yan Li, Lingyun Sun, Yongchuan Tang:
DPC-FSC: An approach of fuzzy semantic cells to density peaks clustering. Inf. Sci. 616: 88-107 (2022) - [c37]Yan Li, Wenqi Huang, Lingyu Liang, Yongchuan Tang, Lingyun Sun:
Density peaks clustering by granular computing with label propagation. ISCID 2022: 221-227 - [c36]Yun Fu, Yongchuan Tang, Deyun Zhou:
A new generation method of basic probability assignment based on the normal membership function. SMC 2022: 385-390 - [c35]Xu Zhang, Yongchuan Tang, Deyun Zhou:
A novel conflict measurement method based on cosine similarity and Deng entropy in Dempster-Shafer evidence theory. SMC 2022: 3198-3203 - [c34]Xu Zhang, Yongchuan Tang, Deyun Zhou:
A new correlation belief transfer method in the evidence theory. SMC 2022: 3204-3209 - 2021
- [j55]Ming Jing, Yongchuan Tang:
A new base basic probability assignment approach for conflict data fusion in the evidence theory. Appl. Intell. 51(2): 1056-1068 (2021) - [j54]Yutong Chen, Yongchuan Tang:
Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion. Entropy 23(4): 402 (2021) - [j53]Jingyu Liu, Yongchuan Tang:
Conflict Data Fusion in a Multi-Agent System Premised on the Base Basic Probability Assignment and Evidence Distance. Entropy 23(7): 820 (2021) - [j52]Ailin Zhu, Zexi Hua, Yu Shi, Yongchuan Tang, Lingwei Miao:
An Improved K-Means Algorithm Based on Evidence Distance. Entropy 23(11): 1550 (2021) - [j51]Yongchuan Tang, Dongdong Wu, Zijing Liu:
A new approach for generation of generalized basic probability assignment in the evidence theory. Pattern Anal. Appl. 24(3): 1007-1023 (2021) - [j50]Qiang Zhang, Hao Li, Rongfei Li, Yongchuan Tang:
An improved measure for belief structure in the evidence theory. PeerJ Comput. Sci. 7: e710 (2021) - [c33]Zejian Li, Jingyu Wu, Immanuel Koh, Yongchuan Tang, Lingyun Sun:
Image Synthesis from Layout with Locality-Aware Mask Adaption. ICCV 2021: 13799-13808 - [c32]Shuaihong Wu, Yongchuan Tang:
A new evidence reliability coefficient for conflict data fusion and its application in classification. SMC 2021: 691-696 - [c31]Yongchuan Tang:
An adaptive coordinator for multi-variable controller via dynamic belief assignment. SMC 2021: 3505-3510 - 2020
- [j49]Rongfei Li, Hao Li, Yongchuan Tang:
An Improved Method to Manage Conflict Data Using Elementary Belief Assignment Function in the Evidence Theory. IEEE Access 8: 37926-37932 (2020) - [j48]Haixia Zheng, Yongchuan Tang:
A Novel Failure Mode and Effects Analysis Model Using Triangular Distribution-Based Basic Probability Assignment in the Evidence Theory. IEEE Access 8: 66813-66827 (2020) - [j47]Jintao Meng, Dongmei Fu, Yongchuan Tang:
Belief-peaks clustering based on fuzzy label propagation. Appl. Intell. 50(4): 1259-1271 (2020) - [j46]Shijie Li, Yongchuan Tang:
A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile. Comput. Math. Methods Medicine 2020: 5013249:1-5013249:9 (2020) - [j45]Dongdong Wu, Zijing Liu, Yongchuan Tang:
A new classification method based on the negation of a basic probability assignment in the evidence theory. Eng. Appl. Artif. Intell. 96: 103985 (2020) - [j44]Haixia Zheng, Yongchuan Tang:
Deng Entropy Weighted Risk Priority Number Model for Failure Mode and Effects Analysis. Entropy 22(3): 280 (2020) - [j43]Miao Qin, Yongchuan Tang, Junhao Wen:
An Improved Total Uncertainty Measure in the Evidence Theory and Its Application in Decision Making. Entropy 22(4): 487 (2020) - [j42]Hongli Yuan, Yongchuan Tang:
MADFU: An Improved Malicious Application Detection Method Based on Features Uncertainty. Entropy 22(7): 792 (2020) - [j41]Shuang Ni, Yan Lei, Yongchuan Tang:
Improved Base Belief Function-Based Conflict Data Fusion Approach Considering Belief Entropy in the Evidence Theory. Entropy 22(8): 801 (2020) - [j40]Bin Yang, Dingyi Gan, Yongchuan Tang, Yan Lei:
Incomplete Information Management Using an Improved Belief Entropy in Dempster-Shafer Evidence Theory. Entropy 22(9): 993 (2020) - [j39]Yongchuan Tang, Yunsong Xiao:
Learning hierarchical concepts based on higher-order fuzzy semantic cell models through the feed-upward mechanism and the self-organizing strategy. Knowl. Based Syst. 194: 105506 (2020) - [j38]Dongdong Wu, Yongchuan Tang:
An improved failure mode and effects analysis method based on uncertainty measure in the evidence theory. Qual. Reliab. Eng. Int. 36(5): 1786-1807 (2020) - [c30]Wei Li, Yongxing He, Yanwei Qi, Zejian Li, Yongchuan Tang:
FET-GAN: Font and Effect Transfer via K-shot Adaptive Instance Normalization. AAAI 2020: 1717-1724 - [i3]Dongdong Wu, Zijing Liu, Yongchuan Tang:
A new approach for generation of generalized basic probability assignment in the evidence theory. CoRR abs/2004.02746 (2020) - [i2]Miao Qin, Yongchuan Tang:
Combination of interval-valued belief structures based on belief entropy. CoRR abs/2011.13636 (2020)
2010 – 2019
- 2019
- [j37]Qian Pan, Deyun Zhou, Yongchuan Tang, Xiaoyang Li:
A Novel Antagonistic Weapon-Target Assignment Model Considering Uncertainty and its Solution Using Decomposition Co-Evolution Algorithm. IEEE Access 7: 37498-37517 (2019) - [j36]Jintao Meng, Dongmei Fu, Yongchuan Tang, Tao Yang, Dawei Zhang:
A Novel Semi-Supervised Classification Method Based on Soft Evidential Label Propagation. IEEE Access 7: 62210-62220 (2019) - [j35]Xuelian Zhou, Yongchuan Tang:
A Note on Incomplete Information Modeling in the Evidence Theory. IEEE Access 7: 166410-166414 (2019) - [j34]Qian Pan, Deyun Zhou, Yongchuan Tang, Xiaoyang Li, Jichuan Huang:
A Novel Belief Entropy for Measuring Uncertainty in Dempster-Shafer Evidence Theory Framework Based on Plausibility Transformation and Weighted Hartley Entropy. Entropy 21(2): 163 (2019) - [j33]Ying Zhou, Yongchuan Tang, Xiaozhe Zhao:
A Novel Uncertainty Management Approach for Air Combat Situation Assessment Based on Improved Belief Entropy. Entropy 21(5): 495 (2019) - [j32]Yong-chuan Tang, Jiangjie Huang, Meng-ting Yao, Jia Wei, Wei Li, Yongxing He, Zejian Li:
A review of design intelligence: progress, problems, and challenges. Frontiers Inf. Technol. Electron. Eng. 20(12): 1595-1617 (2019) - [c29]Zejian Li, Yongchuan Tang, Wei Li, Yongxing He:
Learning Disentangled Representation with Pairwise Independence. AAAI 2019: 4245-4252 - 2018
- [j31]Yongchuan Tang, Deyun Zhou, Felix T. S. Chan:
AMWRPN: Ambiguity Measure Weighted Risk Priority Number Model for Failure Mode and Effects Analysis. IEEE Access 6: 27103-27110 (2018) - [j30]Xiaofeng Lv, Deyun Zhou, Yongchuan Tang, Ling Ma:
An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO. Complex. 2018: 3942723:1-3942723:10 (2018) - [j29]Xiaoyang Li, Deyun Zhou, Qian Pan, Yongchuan Tang, Jichuan Huang:
Weapon-Target Assignment Problem by Multiobjective Evolutionary Algorithm Based on Decomposition. Complex. 2018: 8623051:1-8623051:19 (2018) - [j28]Xuelian Zhou, Yongchuan Tang:
Modeling and Fusing the Uncertainty of FMEA Experts Using an Entropy-Like Measure with an Application in Fault Evaluation of Aircraft Turbine Rotor Blades. Entropy 20(11): 864 (2018) - [j27]Zejian Li, Yongchuan Tang:
Comparative density peaks clustering. Expert Syst. Appl. 95: 236-247 (2018) - [j26]Yongchuan Tang, Yunsong Xiao:
Learning disjunctive concepts based on fuzzy semantic cell models through principles of justifiable granularity and maximum fuzzy entropy. Knowl. Based Syst. 161: 268-293 (2018) - [j25]Yongchuan Tang, Deyun Zhou, Felix T. S. Chan:
An Extension to Deng's Entropy in the Open World Assumption with an Application in Sensor Data Fusion. Sensors 18(6): 1902 (2018) - [j24]Zhiming Huang, Wen Jiang, Yongchuan Tang:
A new method to evaluate risk in failure mode and effects analysis under fuzzy information. Soft Comput. 22(14): 4779-4787 (2018) - [c28]Yongchuan Tang, Deyun Zhou, Felix T. S. Chan:
Extending Deng Entropy to the Open World in the Evidence Theory. FUSION 2018: 629-634 - [c27]Zejian Li, Yongchuan Tang, Yongxing He:
Unsupervised Disentangled Representation Learning with Analogical Relations. IJCAI 2018: 2418-2424 - [c26]Linna Zhu, Yongxing He, Yongchuan Tang:
Using Wikipedia to Construct Product Conceptual Space. ISCID (2) 2018: 103-106 - [c25]Ruiming Luo, Shouqian Sun, Xiangyu Zhao, Yuxuan Zhang, Yongchuan Tang:
Adaptive CPG-Based Impedance Control for Assistive Lower Limb Exoskeleton. ROBIO 2018: 685-690 - [i1]Zejian Li, Yongchuan Tang, Yongxing He:
Unsupervised Disentangled Representation Learning with Analogical Relations. CoRR abs/1804.09502 (2018) - 2017
- [j23]Wen Jiang, Chunhe Xie, Miaoyan Zhuang, Yongchuan Tang:
Failure mode and effects analysis based on a novel fuzzy evidential method. Appl. Soft Comput. 57: 672-683 (2017) - [j22]Deyun Zhou, Yongchuan Tang, Wen Jiang:
An Improved Belief Entropy and Its Application in Decision-Making. Complex. 2017: 4359195:1-4359195:15 (2017) - [j21]Yongchuan Tang, Deyun Zhou, Zichang He, Shuai Xu:
An improved belief entropy-based uncertainty management approach for sensor data fusion. Int. J. Distributed Sens. Networks 13(7) (2017) - [j20]Yongchuan Tang, Deyun Zhou, Shuai Xu:
An Improved Physarum Solver for Supply Chain Network with Fuzzy Numbers. Int. J. Unconv. Comput. 13(2): 161-184 (2017) - [j19]Wen Jiang, Chunhe Xie, Yu Luo, Yongchuan Tang:
Ranking Z-numbers with an improved ranking method for generalized fuzzy numbers. J. Intell. Fuzzy Syst. 32(3): 1931-1943 (2017) - [j18]Yongchuan Tang, Yunsong Xiao:
Learning fuzzy semantic cell by principles of maximum coverage, maximum specificity, and maximum fuzzy entropy of vague concept. Knowl. Based Syst. 133: 122-140 (2017) - [j17]Yongchuan Tang, Deyun Zhou, Shuai Xu, Zichang He:
A Weighted Belief Entropy-Based Uncertainty Measure for Multi-Sensor Data Fusion. Sensors 17(4): 928 (2017) - [j16]Yongchuan Tang, Deyun Zhou, Miaoyan Zhuang, Xueyi Fang, Chunhe Xie:
An Improved Evidential-IOWA Sensor Data Fusion Approach in Fault Diagnosis. Sensors 17(9): 2143 (2017) - [c24]Yongchuan Tang, Xueyi Fang, Deyun Zhou, Xiaofeng Lv:
Weighted deng entropy and its application in uncertainty measure. FUSION 2017: 1-5 - 2016
- [j15]Wen Jiang, Chunhe Xie, Miaoyan Zhuang, Yehang Shou, Yongchuan Tang:
Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis. Sensors 16(9): 1509 (2016) - 2015
- [j14]Yongchuan Tang, Jonathan Lawry:
On truth-gaps, truth-gluts, and bipolar propositions. Int. J. Approx. Reason. 56: 137-151 (2015) - 2014
- [b1]Zengchang Qin, Yongchuan Tang:
Uncertainty Modeling for Data Mining - A Label Semantics Approach. Advanced Topics in Science and Technology in China, Springer 2014, ISBN 978-3-642-41250-9, pp. 1-291 - [j13]Yongchuan Tang, Zejian Lee:
How to adjust the distribution of nonzero elements in sparse representation: A granular locality-preserving approach. Inf. Sci. 289: 25-40 (2014) - 2013
- [j12]Fangwei Li, Yongchuan Tang, Jiang Zhu:
Dynamic Resource Access Using Graphical Game in Asymmetric Wireless Networks. J. Networks 8(8): 1845-1851 (2013) - 2012
- [j11]Jonathan Lawry, Yongchuan Tang:
On truth-gaps, bipolar belief and the assertability of vague propositions. Artif. Intell. 191-192: 20-41 (2012) - [j10]Yongchuan Tang, Jonathan Lawry:
Information cells and information cell mixture models for concept modelling. Ann. Oper. Res. 195(1): 311-323 (2012) - [j9]Yongchuan Tang, Jonathan Lawry:
A bipolar model of vague concepts based on random set and prototype theory. Int. J. Approx. Reason. 53(6): 867-879 (2012) - 2011
- [c23]Feng Liu, Yongchuan Tang, Qian Qi:
Stabilize the planar single inverted pendulum based on LQR. ICAL 2011: 238-242 - [c22]Qian Qi, Dongmei Deng, Feng Liu, Yongchuan Tang:
Stabilization of the double inverted pendulum based on discrete-time model predictive control. ICAL 2011: 243-247 - [c21]Yongchuan Tang, Jonathan Lawry:
Bipolar Semantic Cells: An Interval Model for Linguistic Labels. IUKM 2011: 60-71 - [e2]Yongchuan Tang, Van-Nam Huynh, Jonathan Lawry:
Integrated Uncertainty in Knowledge Modelling and Decision Making - International Symposium, IUKM 2011, Hangzhou, China, October 28-30, 2011. Proceedings. Lecture Notes in Computer Science 7027, Springer 2011, ISBN 978-3-642-24917-4 [contents] - 2010
- [j8]Yongchuan Tang, Jonathan Lawry:
A prototype-based rule inference system incorporating linear functions. Fuzzy Sets Syst. 161(21): 2831-2853 (2010) - [j7]Jonathan Lawry, Yongchuan Tang:
Granular Knowledge Representation and Inference Using Labels and Label Expressions. IEEE Trans. Fuzzy Syst. 18(3): 500-514 (2010) - [c20]Yongchuan Tang, Jonathan Lawry:
Information Cell Mixture Models: The Cognitive Representations of Vague Concepts. IUM 2010: 371-382
2000 – 2009
- 2009
- [j6]Jonathan Lawry, Yongchuan Tang:
Uncertainty modelling for vague concepts: A prototype theory approach. Artif. Intell. 173(18): 1539-1558 (2009) - [j5]Yongchuan Tang, Jonathan Lawry:
Linguistic modelling and information coarsening based on prototype theory and label semantics. Int. J. Approx. Reason. 50(8): 1177-1198 (2009) - [c19]Xiaoyu Sun, Yongchuan Tang:
Automatic Music Emotion Classification Using a New Classification Algorithm. ISCID (2) 2009: 540-542 - [c18]Liang Zhao, Yongchuan Tang:
Comparison of MTR Escape Design in Different Regions. ISCID (2) 2009: 557-560 - [p1]Jonathan Lawry, Yongchuan Tang:
A Random Set and Prototype Theory Model of Linguistic Query Evaluation. Scalable Fuzzy Algorithms for Data Management and Analysis 2009: 159-178 - [e1]Yongchuan Tang, Jonathan Lawry:
2009 Second International Symposium on Computational Intelligence and Design, ISCID 2009, Changsha, Hunan, China, 12-14 December 2009, 2 Volumes. IEEE Computer Society 2009, ISBN 978-0-7695-3865-5 [contents] - 2008
- [j4]Yongchuan Tang:
A Collective Decision Model Involving Vague Concepts and Linguistic Expressions. IEEE Trans. Syst. Man Cybern. Part B 38(2): 421-428 (2008) - [c17]Jonathan Lawry, Yongchuan Tang:
Relating Prototype Theory and Label Semantics. SMPS 2008: 35-42 - 2007
- [c16]Hexin Lv, Ning Qiu, Yongchuan Tang:
Updating Probabilistic Knowledge Using Imprecise and Uncertain Evidence. ICNC (4) 2007: 624-628 - [c15]Hexin Lv, Bin Zhu, Yongchuan Tang:
Fuzzy Classifier with Probabilistic IF-THEN Rules. IFSA (1) 2007: 666-676 - [c14]Hexin Lv, Bin Zhu, Yongchuan Tang:
Conditional Dempster-Shafer Theory for Uncertain Knowledge Updating. IFSA (1) 2007: 767-777 - 2006
- [j3]Yongchuan Tang, Jiacheng Zheng:
Linguistic modelling based on semantic similarity relation among linguistic labels. Fuzzy Sets Syst. 157(12): 1662-1673 (2006) - [j2]Yongchuan Tang, Jiacheng Zheng:
Generalized Jeffrey's rule of conditioning and evidence combining rule for a priori probabilistic knowledge in conditional evidence theory. Inf. Sci. 176(11): 1590-1606 (2006) - 2005
- [j1]Yongchuan Tang, Yang Xu:
Application of fuzzy Naive Bayes and a real-valued genetic algorithm in identification of fuzzy model. Inf. Sci. 169(3-4): 205-226 (2005) - [c13]Jiacheng Zheng, Yongchuan Tang:
Fuzzy Inference System with Probability Factor and Its Application in Data Mining. APWeb 2005: 944-949 - [c12]Yongchuan Tang, Jiacheng Zheng:
Dempster Conditioning and Conditional Independence in Evidence Theory. Australian Conference on Artificial Intelligence 2005: 822-825 - [c11]Jiacheng Zheng, Yongchuan Tang:
One Generalization of the Naive Bayes to Fuzzy Sets and the Design of the Fuzzy Naive Bayes Classifier. IWINAC (2) 2005: 281-290 - 2004
- [c10]Yangguang Liu, Qi Chen, Yongchuan Tang, Qinming He:
An Incremental Updating Method for Support Vector Machines. APWeb 2004: 426-435 - [c9]Yongchuan Tang, Shouqian Sun, Yangguang Liu:
Conditional Evidence Theory and Its Application in Knowledge Discovery. APWeb 2004: 500-505 - [c8]Jiacheng Zheng, Yongchuan Tang:
Fuzzy Modeling Incorporated with Fuzzy D-S Theory and Fuzzy Naive Bayes. Australian Conference on Artificial Intelligence 2004: 816-827 - [c7]Yongchuan Tang, Jiacheng Zheng, Yangguang Liu, Shouqian Sun:
Belief measures conditioned on random set. SMC (3) 2004: 2319-2325 - [c6]Yangguang Liu, Qinming He, Yongchuan Tang:
Support vector pursuit learning. SMC (6) 2004: 5841-5846 - [c5]Yongchuan Tang, Shouqian Sun:
A Mixture Model of Classical Fuzzy Classifiers. WAIM 2004: 616-621 - 2003
- [c4]Xiaoping Qiu, Dan Meng, Yongchuan Tang, Yang Xu:
Multilayered fuzzy clustering method based on distance and density. SMC 2003: 1417-1422 - 2001
- [c3]Wuming Pan, Yongchuan Tang, Yang Xu, Keyun Qin:
Local relation mapping theory of fuzzy reasoning. SMC 2001: 2145-2150 - [c2]Wuming Pan, Yongchuan Tang, Yang Xu, Keyun Qin:
Local relations hold reasoning. SMC 2001: 2151-2156 - 2000
- [c1]Yongchuan Tang, Tianmin Huang:
The driven genetic selection mechanism. SMC 2000: 3873-3876
Coauthor Index
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