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Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases (Advances in Fuzzy Systems - Applications & Theory) [Paperback]

By Oscar Cordon (Author), Francisco Herrera (Author), Frank Hoffmann (Author) & Luis Magdalena (Author)
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Item description for Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases (Advances in Fuzzy Systems - Applications & Theory) by Oscar Cordon, Francisco Herrera, Frank Hoffmann & Luis Magdalena...

A number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. This volume explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the 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 Systems" 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 aims to provide a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms - specifically for probabilists, analysts, statisticians and mathematicians.



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Item Specifications...


Studio: World Scientific Publishing Company
Pages   488
Est. Packaging Dimensions:   Length: 8.48" Width: 6.01" Height: 1.01"
Weight:   1.41 lbs.
Binding  Softcover
Release Date   Feb 15, 2002
Publisher   World Scientific Publishing Company
ISBN  9810240171  
ISBN13  9789810240172  


Availability  0 units.


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Product Categories

1Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Computer Mathematics
2Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > General
3Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Machine Learning
4Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Theory of Computing
5Books > Subjects > Computers & Internet > Computer Science > Software Engineering > Information Systems
6Books > Subjects > Computers & Internet > General
7Books > Subjects > Computers & Internet > Programming > Algorithms > Fuzzy Logic



Reviews - What do customers think about Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases (Advances in Fuzzy Systems - Applications & Theory)?

A major source on genetic fuzzy systems  Sep 27, 2001
The volume brings an outstanding presentation of the major issues, ideas, concepts and algorithms to design and develop fuzzy systems using gentic algorithms. A field of major relevance for researchers and practioners, genetic fuzzy systems provides a major methodological substract of significant impact in practice. The book is unique in its contents and presentation. Chapters begin with the key concepts and smoothly grows to advanced concepts in a clear and very understandable and motivating way. The material mirrors the state of the art in the area of genetic fuzzy systems and contains the most recent results available until its publication. Written by renowned, internationally recognized researchers, the book is mandatory to all who are interested in the field of computational intelligence, its foundations and applications.
 
Summary of contents by the author  Sep 19, 2001
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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