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Daniel Urda Muñoz
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2020 – today
- 2024
[j22]Álvaro Herrero, Daniel Urda
, Esteban Jove, Mariusz Topolski, Emilio Corchado:
Soft-Computing Techniques to Address Industrial and Environmental Challenges. Cybern. Syst. 55(6): 1311-1313 (2024)- [j21]Nuño Basurto, Carlos Cambra Baseca, Álvaro Herrero, Daniel Urda:
A Clustering Extension of HUEPs for the Analysis of Performance Anomalies in Robots. Cybern. Syst. 55(6): 1357-1377 (2024) - [j20]Roberto Magán-Carrión, Daniel Urda, Ignacio Díaz-Cano, Bernabé Dorronsoro:
Evaluating the Impact of Different Feature as a Counter Data Aggregation approaches on the Performance of NIDSs and Their Selected Features. Log. J. IGPL 32(2): 263-280 (2024) - [j19]Nuño Basurto, Diego García-Prieto, Héctor Quintián, Daniel Urda, José Luís Calvo-Rolle, Emilio Corchado:
Beta-Hebbian Learning to enhance unsupervised exploratory visualizations of Android malware families. Log. J. IGPL 32(2): 306-320 (2024) - [c38]Nuria Velasco-Pérez, Samuel Lozano-Juárez, Lucía Núñez-Calvo, Nuño Basurto, Juan Arnaez, Daniel Urda:
A Computer Vision Approach to Detect Facial Characteristics Related to Encephalopathy in Term Infants. HAIS (1) 2024: 98-109 - [c37]Lucía Núñez-Calvo, Nuria Velasco-Pérez, Samuel Lozano-Juárez, Álvaro Herrero, Juan Arnaez, Daniel Urda:
Neonates Crying Detection Through Feature Extraction and Machine Learning Methods. HAIS (1) 2024: 275-285 - 2023
- [j18]Daniel Urda, Patricia Ruiz, El-Ghazali Talbi, Pascal Bouvry, Jamal Toutouh:
Editorial of the Special Issue Intelligent Solutions for Efficient Logistics and Sustainable Transportation. Appl. Soft Comput. 133: 109961 (2023) - [j17]José Antonio Moscoso López, Javier González-Enrique, Daniel Urda, Juan Jesús Ruiz-Aguilar, Ignacio J. Turias:
Hourly pollutants forecasting using a deep learning approach to obtain the AQI. Log. J. IGPL 31(4): 722-738 (2023) - [c36]Marcos Severt, Roberto Casado-Vara, Ángel Martín del Rey, Nuño Basurto, Daniel Urda, Álvaro Herrero:
Benchmarking Classifiers for DDoS Attack Detection in Industrial IoT Networks. CISIS-ICEUTE 2023: 167-176 - [c35]Samuel Lozano-Juárez, Nuria Velasco-Pérez, Ian Roberts, Jerónimo Bernal, Nuño Basurto, Daniel Urda, Álvaro Herrero:
Convolutional Neural Networks for Diabetic Retinopathy Grading from iPhone Fundus Images. HAIS 2023: 685-697 - [c34]Arantxa M. Ortega León, Roa'a Khaled, María Inmaculada Rodríguez-García, Daniel Urda, Ignacio J. Turias:
A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data. IWBBIO (1) 2023: 419-430 - [c33]Ángel Arroyo, Beatriz Gil-Arroyo, Daniel Urda, Carlos Cambra, Álvaro Herrero:
Missing Values Imputation for Visualizing the Air Quality Evolution During the COVID-19 Pandemic in Madrid. SOCO (1) 2023: 196-205 - [c32]Nuria Velasco-Pérez, Samuel Lozano-Juárez, Beatriz Gil-Arroyo, Juan Marcos Sanz, Nuño Basurto, Daniel Urda, Álvaro Herrero:
Defect Detection in Batavia Woven Fabrics by Means of Convolutional Neural Networks. SOCO (2) 2023: 205-215 - 2022
- [j16]Álvaro Herrero, Daniel Urda, Javier Sedano, Héctor Quintián, Emilio Corchado:
Computational intelligence applied to cybersecurity. Expert Syst. J. Knowl. Eng. 39(9) (2022) - [j15]Héctor Quintián, Esteban Jove, José Luís Casteleiro-Roca, Daniel Urda, Ángel Arroyo, José Luís Calvo-Rolle, Álvaro Herrero, Emilio Corchado:
Advanced Visualization of Intrusions in Flows by Means of Beta-Hebbian Learning. Log. J. IGPL 30(6): 1056-1073 (2022) - [j14]Javier Sedano, Daniel Urda, José Luís Calvo-Rolle, Héctor Quintián, Emilio Corchado:
Special issue SOCO 2020: New trends in soft computing and its application in industrial and environmental problems. Neurocomputing 504: 187-188 (2022) - [j13]Roberto Magán-Carrión, Daniel Urda, Ignacio Díaz-Cano, Bernabé Dorronsoro:
Improving the Reliability of Network Intrusion Detection Systems Through Dataset Integration. IEEE Trans. Emerg. Top. Comput. 10(4): 1717-1732 (2022) - [c31]Nuño Basurto, Álvaro Michelena, Daniel Urda, Héctor Quintián, José Luís Calvo-Rolle, Álvaro Herrero:
Dimensionality-Reduction Methods for the Analysis of Web Traffic. CISIS-ICEUTE 2022: 62-72 - [c30]Daniel Urda, Nuño Basurto, Meelis Kull, Álvaro Herrero:
Evaluating Classifiers' Performance to Detect Attacks in Website Traffic. CISIS-ICEUTE 2022: 205-215 - [c29]Roberto Alcalde, Daniel Urda, Carlos Alonso de Armiño, Santiago García, Manuel Manzanedo, Álvaro Herrero:
Non-linear Neural Models to Predict HRC Steel Price in Spain. SOCO 2022: 186-194 - [c28]Damián Nimo, Javier González-Enrique, David Perez, Juan Almagro, Daniel Urda, Ignacio J. Turias:
A Virtual Sensor Approach to Estimate the Stainless Steel Final Chemical Characterisation. SOCO 2022: 350-360 - 2021
- [j12]Michal Choras, Konstantinos P. Demestichas, Agata Gielczyk, Álvaro Herrero, Pawel Ksieniewicz, Konstantina Remoundou, Daniel Urda, Michal Wozniak:
Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study. Appl. Soft Comput. 101: 107050 (2021) - [j11]José Antonio Moscoso López, Daniel Urda, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Ignacio J. Turias:
A machine learning-based forecasting system of perishable cargo flow in maritime transport. Neurocomputing 452: 487-497 (2021) - [j10]Juan Jesús Ruiz-Aguilar, Ignacio Turias, Javier González-Enrique, Daniel Urda, David A. Elizondo:
A permutation entropy-based EMD-ANN forecasting ensemble approach for wind speed prediction. Neural Comput. Appl. 33(7): 2369-2391 (2021) - [j9]Daniel Urda, Francisco J. Veredas, Javier González-Enrique, Juan J. Ruiz-Aguilar, José M. Jerez, Ignacio J. Turias:
Deep neural networks architecture driven by problem-specific information. Neural Comput. Appl. 33(15): 9403-9423 (2021) - [j8]Javier González-Enrique, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso López, Daniel Urda, Lipika Deka, Ignacio J. Turias:
Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO2 (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain). Sensors 21(5): 1770 (2021) - [c27]Roberto Magán-Carrión, Daniel Urda, Ignacio Díaz-Cano, Bernabé Dorronsoro:
Assessing the Impact of Batch-Based Data Aggregation Techniques for Feature Engineering on Machine Learning-Based Network IDSs. CISIS-ICEUTE 2021: 116-125 - [c26]Nuño Basurto, Héctor Quintián, Daniel Urda, José Luís Calvo-Rolle, Álvaro Herrero, Emilio Corchado:
Advanced 3D Visualization of Android Malware Families. CISIS-ICEUTE 2021: 167-177 - [e4]Álvaro Herrero, Carlos Cambra, Daniel Urda, Javier Sedano, Héctor Quintián, Emilio Corchado:
13th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2020, Burgos, Spain, September 2020. Advances in Intelligent Systems and Computing 1267, Springer 2021, ISBN 978-3-030-57804-6 [contents] - [e3]Álvaro Herrero, Carlos Cambra, Daniel Urda, Javier Sedano, Héctor Quintián, Emilio Corchado:
The 11th International Conference on EUropean Transnational Educational, ICEUTE 2020, Burgos, Spain, September 16-18, 2020. Advances in Intelligent Systems and Computing 1266, Springer 2021, ISBN 978-3-030-57798-8 [contents] - [e2]Álvaro Herrero, Carlos Cambra, Daniel Urda, Javier Sedano, Héctor Quintián, Emilio Corchado:
15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020, Burgos, Spain, 16-18 September 2020. Advances in Intelligent Systems and Computing 1268, Springer 2021, ISBN 978-3-030-57801-5 [contents] - [i2]Michal Choras, Konstantinos P. Demestichas, Agata Gielczyk, Álvaro Herrero, Pawel Ksieniewicz, Konstantina Remoundou, Daniel Urda, Michal Wozniak:
Advanced Machine Learning Techniques for Fake News (Online Disinformation) Detection: A Systematic Mapping Study. CoRR abs/2101.01142 (2021) - [i1]Roberto Magán-Carrión, Daniel Urda, Ignacio Díaz-Cano, Bernabé Dorronsoro:
Improving the Reliability of Network Intrusion Detection Systems through Dataset Integration. CoRR abs/2112.02080 (2021) - 2020
- [j7]Juan Jesús Ruiz-Aguilar, Daniel Urda, José Antonio Moscoso López, Javier González-Enrique, Ignacio J. Turias:
A freight inspection volume forecasting approach using an aggregation/disaggregation procedure, machine learning and ensemble models. Neurocomputing 391: 282-291 (2020) - [j6]Francisco J. Veredas, Daniel Urda, José Luis Subirats, Francisco R. Cantón, Juan Carlos Aledo:
Combining feature engineering and feature selection to improve the prediction of methionine oxidation sites in proteins. Neural Comput. Appl. 32(2): 323-334 (2020) - [c25]Héctor Quintián, Esteban Jove, José Luís Casteleiro-Roca, Daniel Urda, Ángel Arroyo, José Luís Calvo-Rolle, Álvaro Herrero, Emilio Corchado:
Beta-Hebbian Learning for Visualizing Intrusions in Flows. CISIS 2020: 446-459 - [c24]Ángel Arroyo, Secil Bayraktar, Carlos Cambra, Daniel Urda, Álvaro Herrero:
Trends and Patterns of International Student Mobility: The Case of Bachelor's Degrees in Computer Science at the University of Burgos. ICEUTE 2020: 142-153 - [c23]Damián Nimo, Bernabé Dorronsoro, Ignacio J. Turias, Daniel Urda:
Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance. OLA 2020: 58-68 - [c22]Juan Jesús Ruiz-Aguilar, Daniel Urda, José Antonio Moscoso López, Javier González-Enrique, Ignacio J. Turias:
Container Demand Forecasting at Border Posts of Ports: A Hybrid SARIMA-SOM-SVR Approach. OLA 2020: 69-81 - [c21]José Antonio Moscoso López, Daniel Urda, Javier González-Enrique, Juan Jesús Ruiz-Aguilar, Ignacio J. Turias:
Hourly Air Quality Index (AQI) Forecasting Using Machine Learning Methods. SOCO 2020: 123-132 - [e1]Bernabé Dorronsoro, Patricia Ruiz, Juan Carlos de la Torre, Daniel Urda, El-Ghazali Talbi:
Optimization and Learning - Third International Conference, OLA 2020, Cádiz, Spain, February 17-19, 2020, Proceedings. Communications in Computer and Information Science 1173, Springer 2020, ISBN 978-3-030-41912-7 [contents]
2010 – 2019
- 2019
- [c20]Héctor Mesa, Daniel Urda, Juan J. Ruiz-Aguilar, José Antonio Moscoso López, Juan Almagro, Patricia Acosta, Ignacio J. Turias:
A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel. HAIS 2019: 504-513 - [c19]José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Daniel Urda, Héctor Mesa, Ignacio J. Turias:
Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks. HAIS 2019: 563-574 - [c18]Guillermo López-García, José M. Jerez, Daniel Urda, Francisco J. Veredas:
MetODeep: A Deep Learning Approach for Prediction of Methionine Oxidation Sites in Proteins. IJCNN 2019: 1-8 - [c17]Daniel Urda Muñoz, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Ignacio Turias Domínguez:
A Deep Ensemble Neural Network Approach to Improve Predictions of Container Inspection Volume. IWANN (1) 2019: 806-817 - [c16]José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, Daniel Urda, Javier González-Enrique, Ignacio José Turias:
Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar. IWANN (1) 2019: 818-831 - [c15]Javier González-Enrique, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso López, Steffanie Van Roode, Daniel Urda, Ignacio J. Turias:
A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations. IWANN (1) 2019: 856-867 - [c14]Daniel Urda, Francisco J. Veredas, Ignacio Turias, Leonardo Franco:
Addition of Pathway-Based Information to Improve Predictions in Transcriptomics. IWBBIO (2) 2019: 200-208 - 2018
- [j5]Daniel Urda, Francisco Aragón, Rocío Bautista, Leonardo Franco, Francisco J. Veredas, Manuel Gonzalo Claros, José Manuel Jerez:
BLASSO: integration of biological knowledge into a regularized linear model. BMC Syst. Biol. 12(5): 13-26 (2018) - [c13]Daniel Urda, José M. Jerez, Ignacio J. Turias:
Data Dimension and Structure Effects in Predictive Performance of Deep Neural Networks. SoMeT 2018: 361-372 - [c12]Francisco J. Moreno-Barea, Fiammetta Strazzera, José M. Jerez, Daniel Urda, Leonardo Franco:
Forward Noise Adjustment Scheme for Data Augmentation. SSCI 2018: 728-734 - 2017
- [c11]Daniel Urda, Rafael Marcos Luque Baena, Leonardo Franco, José M. Jerez, Noelia Sánchez-Maroño:
Machine learning models to search relevant genetic signatures in clinical context. IJCNN 2017: 1649-1656 - [c10]Daniel Urda, Julio Montes-Torres, Fernando Moreno, Leonardo Franco, José M. Jerez:
Deep Learning to Analyze RNA-Seq Gene Expression Data. IWANN (2) 2017: 50-59 - [c9]Daniel Urda, Francisco Aragón, Leonardo Franco, Francisco J. Veredas, José M. Jerez:
L_1 L 1 -regularization Model Enriched with Biological Knowledge. IWBBIO (1) 2017: 579-590 - [c8]Daniel Urda, Leonardo Franco, José M. Jerez:
Classification of high dimensional data using LASSO ensembles. SSCI 2017: 1-7 - 2016
- [j4]Francisco Ortega-Zamorano, José M. Jerez, Daniel Urda, Rafael M. Luque-Baena, Leonardo Franco:
Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers. IEEE Trans. Neural Networks Learn. Syst. 27(9): 1840-1850 (2016) - 2014
- [j3]Rafael Marcos Luque Baena, Daniel Urda, M. Gonzalo Claros, Leonardo Franco, José M. Jerez:
Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords. J. Biomed. Informatics 49: 32-44 (2014) - [c7]Daniel Urda, Simon J. Chambers, Ian H. Jarman, Paulo J. G. Lisboa, Leonardo Franco, José M. Jerez:
Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures. CIBB 2014: 199-206 - 2013
- [j2]Daniel Urda, Nuria Ribelles, José Luis Subirats, Leonardo Franco, Emilio Alba, José Manuel Jerez:
Addressing critical issues in the development of an Oncology Information System. Int. J. Medical Informatics 82(5): 398-407 (2013) - [c6]Daniel Urda, Ciprian Dobre, Florin Pop:
Storing Location-Aware Data in Mobile Distributed Systems. ISPDC 2013: 135-142 - [c5]Daniel Urda, Rafael Marcos Luque, María Jesús Jiménez-Come, Ignacio Turias Domínguez, Leonardo Franco, José Manuel Jerez:
A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel. IWANN (1) 2013: 88-95 - [c4]José Luis Subirats, Rafael Marcos Luque Baena, Daniel Urda, Francisco Ortega-Zamorano, José Manuel Jerez, Leonardo Franco:
Committee C-Mantec: A Probabilistic Constructive Neural Network. IWANN (1) 2013: 339-346 - [c3]Rafael Marcos Luque Baena, Daniel Urda, José Luis Subirats, Leonardo Franco, José M. Jerez:
Analysis of Cancer Microarray Data using Constructive Neural Networks and Genetic Algorithms. IWBBIO 2013: 55-63 - 2012
- [j1]Daniel Urda, José Luis Subirats, Pedro J. García-Laencina, Leonardo Franco, José-Luis Sancho-Gómez, José Manuel Jerez:
WIMP: Web server tool for missing data imputation. Comput. Methods Programs Biomed. 108(3): 1247-1254 (2012) - 2011
- [c2]Yasel Couce, Leonardo Franco, Daniel Urda, José Luis Subirats, José M. Jerez:
Hybrid (Generalization-Correlation) Method for Feature Selection in High Dimensional DNA Microarray Prediction Problems. IWANN (2) 2011: 202-209 - 2010
- [c1]Daniel Urda, José Luis Subirats, Leonardo Franco, José Manuel Jerez:
Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles. IEA/AIE (1) 2010: 317-326
Coauthor Index
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last updated on 2024-11-07 21:35 CET by the dblp team
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