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    COMPENSATORY GENETIC FUZZY NEURAL NETWORKS AND THEIR APPLICATIONS

    by Yanqing Zhang (University of South Florida & Georgia Southwestern State University) & Abraham Kandel (University of South Florida & Tel-Aviv University)

    About Yanqing Zhang
     

    About Abraham Kandel
     

    This book presents a powerful hybrid intelligent system based on fuzzy logic, neural networks, genetic algorithms and related intelligent techniques. The new compensatory genetic fuzzy neural networks have been widely used in fuzzy control, nonlinear system modeling, compression of a fuzzy rule base, expansion of a sparse fuzzy rule base, fuzzy knowledge discovery, time series prediction, fuzzy games and pattern recognition. This effective soft computing system is able to perform both linguistic-word-level fuzzy reasoning and numerical-data-level information processing. The book also proposes various novel soft computing techniques.

     
    Contents:
    • Fuzzy Compensation Principles
    • Normal Fuzzy Reasoning Methodology
    • Compensatory Genetic Fuzzy Neural Networks
    • Fuzzy Knowledge Rediscovery in Fuzzy Rule Bases
    • Fuzzy Cart-Pole Balancing Control Systems
    • Fuzzy Knowledge Compression and Expansion
    • Highly Nonlinear System Modeling and Prediction
    • Fuzzy Moves in Fuzzy Games
    • Genetic Neuro-Fuzzy Pattern Recognition
    • Constructive Approach to Modeling Fuzzy Systems
     
    Readership: Graduate students, researchers and experts in fuzzy logic, neural networks and genetic algorithms, and their applications.
     


     
    200pp    Pub. date: Aug 1998  
    ISBN:   978-981-02-3349-5
    981-02-3349-3
       US$58 / £39

     


    200pp    Pub. date: Aug 1998  
    ISBN:   978-981-279-767-4(ebook)
    981-279-767-X(ebook)
       US$76 / £45

     


     

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