Publikationen, an denen er mitarbeitet JORGE CASILLAS BARRANQUERO (17)

2007

  1. Local identification of prototypes for genetic learning of accurate TSK fuzzy rule-based systems

    International Journal of Intelligent Systems, Vol. 22, Núm. 9, pp. 909-941

2006

  1. Hybrid learning models to get the interpretability - Accuracy trade-off in fuzzy modeling

    Soft Computing, Vol. 10, Núm. 9, pp. 717-734

2005

  1. A genetic rule weighting and selection process for fuzzy control of heating, ventilating and air conditioning systems

    Engineering Applications of Artificial Intelligence, Vol. 18, Núm. 3, pp. 279-296

  2. Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction

    IEEE Transactions on Fuzzy Systems, Vol. 13, Núm. 1, pp. 13-29

  3. Learning cooperative linguistic fuzzy rules using the best-worst ant system algorithm

    International Journal of Intelligent Systems, Vol. 20, Núm. 4, pp. 433-452

2003

  1. Fuzzy control of HVAC systems optimized by genetic algorithms

    Applied Intelligence, Vol. 18, Núm. 2, pp. 155-177

  2. Linguistic modeling with weighted double-consequent fuzzy rules based on cooperative coevolutionary learning

    Integrated Computer-Aided Engineering, Vol. 10, Núm. 4, pp. 343-355

2002

  1. COR: A methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules

    IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 32, Núm. 4, pp. 526-537

  2. Cooperative coevolution for learning fuzzy rule-based systems

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Hybridizing hierarchical and weighted linguistic rules

    Proceedings of the ACM Symposium on Applied Computing

  4. Improving simple linguistic fuzzy models by means of the weighted COR methodology

    Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

  5. Some relationships between fuzzy and random set-based classifiers and models

    International Journal of Approximate Reasoning, Vol. 29, Núm. 2, pp. 175-213

  6. Techniques for designing and refining linguistic fuzzy models to improve their accuracy

    Intelligent Systems: Technology and Applications, Six Volume Set (CRC Press), pp. II-143-II-180

2001

  1. Building fuzzy graphs: Features and taxonomy of learning for non-grid-oriented fuzzy rule-based systems

    Journal of Intelligent and Fuzzy Systems, Vol. 11, Núm. 3-4, pp. 99-119

  2. Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems

    Information Sciences

  3. Genetic tuning of fuzzy rule-based systems integrating linguistic hedges

    Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

  4. Improvement to the cooperative rules methodology by using the ant colony system algorithm

    Mathware & soft computing: The Magazine of the European Society for Fuzzy Logic and Technology, Vol. 8, Núm. 3, pp. 321-335