Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases

Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases

by Oscar Cordon, Francisco Herrera, Frank Hoffmann, Frank Hoffmann
     
 

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ISBN-10: 9810240163

ISBN-13: 9789810240165

Pub. Date: 07/13/2001

Publisher: World Scientific Publishing Company, Incorporated

In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that

Overview

In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas.Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.

Product Details

ISBN-13:
9789810240165
Publisher:
World Scientific Publishing Company, Incorporated
Publication date:
07/13/2001
Series:
Advances in Fuzzy Systems Series
Pages:
488

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