Compensatory genetic fuzzy neural networks and their applications

Bibliographic Information

Compensatory genetic fuzzy neural networks and their applications

Yanqing Zhang, Abraham Kandel

(Series in machine perception and artificial intelligence / editors, H. Bunke, P.S.P. Wang, v. 30)

World Scientific, c1998

Available at  / 9 libraries

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Note

Includes bibliographical references (p. 173-181) and index

Description and Table of Contents

Description

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.

Table of Contents

  • Fuzzy compensation principles
  • normal fuzzy reasoning methodology
  • compensatory genetic fuzzy neural networks
  • fuzzy knowledge rediscovery in fuzzy rule bases
  • fuzzy cat-pole balancing control systems
  • fuzzy knowledge compression and expansion
  • highly nonlinear system modelling and prediction
  • fuzzy moves in fuzzy games
  • genetic neuro-fuzzy pattern recognition
  • constructive approach to modelling fuzzy systems.

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