Computer
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Genetic Algorithms: Concepts and Designs with Disk
Genetic Algorithms: Concepts and Designs with Disk
Knowledge Representation in Fuzzy Logic
IEEE Transactions on Knowledge and Data Engineering
Hybrid Intelligent Systems: Analysis and Design (Studies in Fuzziness and Soft Computing)
Hybrid Intelligent Systems: Analysis and Design (Studies in Fuzziness and Soft Computing)
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing)
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Analysis and Design of Intelligent Systems Using Soft Computing Techniques
Analysis and Design of Intelligent Systems Using Soft Computing Techniques
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Information Sciences: an International Journal
MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
Optimization of type-2 fuzzy systems based on bio-inspired methods: A concise review
Information Sciences: an International Journal
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Engineering Applications of Artificial Intelligence
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We describe in this paper a new evolutionary method for the optimization of a modular neural network for multimodal biometry The proposed evolutionary method produces the best architecture of the modular neural network (number of modules, layers and neurons) and fuzzy inference systems (memberships functions and rules) as fuzzy integration methods. The integration of responses in the modular neural network is performed by using type-1 and type-2 fuzzy inference systems.