Fuzzy and Neural Approaches in Engineering / Edition 1

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Fuzzy and Neural Approaches in Engineering presents a detailed examination of the fundamentals of fuzzy systems and neural networks and then joins them synergistically - combining the feature extraction and modeling capabilities of the neural network with the representation capabilities of fuzzy systems. Exploring the value of relating genetic algorithms and expert systems to fuzzy and neural technologies, this forward-thinking text highlights an entire range of dynamic possibilities within soft computing. With examples of specifically designed to illuminate key concepts and overcome the obstacles of notation and overly mathematical presentations often encountered in other sources, plus tables, figures, and an up-to-date bibliography, this unique work is both an important reference and a practical guide to neural networks and fuzzy systems.
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Product Details

Meet the Author

LEFTERI H. TSOUKALAS, PhD, is on the faculty of the School of Nuclear Engineering at Purdue University and is an active industrial consultant and speaker. ROBERT E. UHRIG, PhD, holds a joint appointment as Distinguished Professor in the Nuclear Engineering Department at the University of Tennessee and Distinguished Scientist in the Instrumentation and Control Division at the Oak Ridge National Laboratory. He is the author of Random Noise Techniques in Nuclear Reactor Systems.

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Table of Contents

1 Introduction to Hybrid Artificial Intelligence Systems 1
2 Foundations of Fuzzy Approaches 13
3 Fuzzy Relations 49
4 Fuzzy Numbers 77
5 Linguistic Descriptions and Their Analytical Forms 105
6 Fuzzy Control 145
7 Fundamentals of Neural Networks 191
8 Backpropagation and Related Training Algorithms 229
9 Competitive, Associative, and Other Special Neural Networks 289
10 Dynamic Systems and Neural Control 333
11 Practical Aspects of Using Neural Networks 385
12 Fuzzy Methods in Neural Networks 409
13 Neural Methods in Fuzzy Systems 445
14 Selected Hybrid Neurofuzzy Applications 471
15 Dynamic Hybrid Neurofuzzy Systems 493
16 Expert Systems in Neurofuzzy Systems 523
17 Genetic Algorithms 539
18 Epilogue 561
App T Norms and S Norms 567
Index 575
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  • Anonymous

    Posted April 25, 2005

    An excellent book in fuzzy logic and neural network

    This is really an excellent book in fuzzy logic theory and neural network. I am currently doing some study and research on Fuzzy Control, and I had read books on fuzzy logic/control. Most of the book either give too many theoretical explanation (a lot of mathematical equations without further explaination in words/linguistic), or too introductory (too linguistic description). Further more, most books assumed that you have some background in the subject. This is the book which I find that it started with a very simple introduction by explaning symbols used, and illustrated with many examples, which make the reader grasp the concept easily. In other words, the mathematical equations and linguistic description are supporting each other.

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  • Anonymous

    Posted February 25, 2003

    Excellent Book

    This is one of the best books that I've read on FL for an engineer. Great examples and clear and concise writing make this book a great read. You know when you read a novel and you can just blow through 50 pages and understand everything? This book reads like a novel, but has the technical details to educate you.

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