Compensatory Genetic Fuzzy Neural Networks and Their Applications

by Yan-Qing Zhang, 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 PrinciplesNormal Fuzzy Reasoning MethodologyCompensatory Genetic Fuzzy Neural NetworksFuzzy Knowledge Rediscovery in Fuzzy Rule BasesFuzzy Cart-Pole Balancing Control SystemsFuzzy Knowledge Compression and ExpansionHighly Nonlinear System Modeling and PredictionFuzzy Moves in Fuzzy GamesGenetic Neuro-Fuzzy Pattern RecognitionConstructive Approach to Modeling Fuzzy Systems
Readership: Graduate students, researchers and experts in fuzzy logic, neural networks and genetic algorithms, and their applications.

202 pages, ebook

First published January 1, 1998