Flexible Neuro-Fuzzy Systems: Structures, Learning and Performance Evaluation

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Springer Science & Business Media, May 19, 2004 - Computers - 279 pages
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Flexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data.
Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features:

-Provides a framework for unification, construction and development of neuro-fuzzy systems;
-Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation,
-Covers not only advanced topics but also fundamentals of fuzzy sets,
-Includes problems and exercises following each chapter,
-Illustrates the results on a wide variety of simulations,
-Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.

Flexible Neuro-Fuzzy Systems is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.
 

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Contents

FUZZY INFERENCE SYSTEMS
27
Soft fuzzy norms Parameterized triangular norms ORtype systems Compromise systems Summary and discussion Problems FLEXIBLE ORTYPE NE...
75
FLEXIBLE COMPROMISE ANDTYPE NEUROFUZZY SYSTEMS
129
FLEXIBLE LOGICALTYPE NEUROFUZZY SYSTEMS
184
PERFORMANCE COMPARISON OF NEUROFUZZY SYSTEMS 9 1 9 2 9 3 Introduction Comparison charts Summary and discussion
235
APPENDIX
255
BIBLIOGRAPHY
264
INDEX
277
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