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Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases
Contributor(s): Cordon, Oscar (Author), Herrera, Francisco (Author), Hoffmann, Frank (Author)

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 ISBN: 9810240171     ISBN-13: 9789810240172
Publisher: World Scientific Publishing Company
OUR PRICE: $82.65  

Binding Type: Paperback - See All Available Formats & Editions
Published: July 2001
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Annotation: 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.

Click for more in this series: Advances in Fuzzy Systems-Applications and Theory
Additional Information
BISAC Categories:
- Computers | Intelligence (ai) & Semantics
- Technology & Engineering | Robotics
Dewey: 006.3
Series: Advances in Fuzzy Systems-Applications and Theory
Physical Information: 1.03" H x 6.36" W x 8.48" L (1.44 lbs) 488 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
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.
 
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