Computational Intelligence: Concepts to Implementations / Edition 1

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Overview

Russ Eberhart and Yuhui Shi have succeeded in integrating various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook, including lots of practical examples. -Shun-ichi Amari, RIKEN Brain Science Institute, Japan

This book is an excellent choice on its own, but, as in my case, will form the foundation for our advanced graduate courses in the CI disciplines. -James M. Keller, University of Missouri-Columbia

The excellent new book by Eberhart and Shi asserts that computational intelligence rests on a foundation of evolutionary computation. This refreshing view has set the book apart from other books on computational intelligence. The book has an emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field. -Xin Yao, The Centre of Excellence for Research in Computational Intelligence and Applications, Birmingham

The “soft” analytic tools that comprise the field of computational intelligence have matured to the extent that they can, often in powerful combination with one another, form the foundation for a variety of solutions suitable for use by domain experts without extensive programming experience.

Computational Intelligence: Concepts to Implementations provides the conceptual and practical knowledge necessary to develop solutions of this kind. Focusing on evolutionary computation, neural networks, and fuzzy logic, the authors have constructed an approach to thinking about and working with computational intelligence that has, in their extensive experience, proved highly effective.
Features

• Moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific concepts and paradigms that inform the authors’ methodologies.

• Explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation.

• Details the metrics and analytical tools needed to assess the performance of computational intelligence tools.

• Concludes with a series of case studies that illustrate a wide range of successful applications.

• Presents code examples in C and C++.

• Provides, at the end of each chapter, review questions and exercises suitable for graduate students, as well as researchers and practitioners engaged in self-study.

• Makes available, on a companion website, a number of software implementations that can be adapted for real-world applications.

About the Authors
Russell Eberhart is Professor of Electrical and Computer Engineering at Purdue School of Engineering and Technology, and Vice President of Computelligence LLC, in Indianapolis. He and Yuhui Shi are co-authors with Jim Kennedy of Swarm Intelligence (Morgan Kaufmann, 2001). Yuhui Shi is an Embedded System Specialist for Electronic Data Systems, Inc. He is an associate editor of the IEEE Transactions on Evolutionary Computation.

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Editorial Reviews

From the Publisher
Russ Eberhart and Yuhui Shi have succeeded in integrating various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook, including lots of practical examples. Professor Shun-ichi Amari, RIKEN Brain Science Institute, Japan

Computational Intelligence describes a large, diverse, and evolving field of theories and techniques, all inspired in one way or the other by nature. The three pillars of CI, neural networks, fuzzy systems, and evolutionary computation, along with their many variants, interact in meaningful ways to solve very complex problems. This book is an excellent introduction to the field, greatly suited for an advanced undergraduate/ beginning graduate student course, or for an interested scientist or engineer. The authors guide the reader in an easy flowing way through the history and foundational mathematics toward practical implementation of a few fundamental problem-solving systems in each area. In the fuzzy set chapters, they picked the most common application tool, fuzzy rule-based systems, even mixing in evolutionary design into the implementation. This book is an excellent choice on its own, but, as in my case, will form the foundation for our advanced graduate courses in the CI disciplines. James M. Keller, University of Missouri-Columbia

The excellent new book by Eberhart and Shi asserts that computational intelligence rests on a foundation of evolutionary computation. This refreshing view has set the book apart from other books on computational intelligence. The book has an emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field. I am delighted that I have a copy of this book. Professor Xin Yao, The Centre of Excellence for Research in Computational Intelligence and Applications

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Product Details

  • ISBN-13: 9781558607590
  • Publisher: Elsevier Science
  • Publication date: 8/10/2007
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 496
  • Product dimensions: 7.78 (w) x 9.28 (h) x 1.28 (d)

Meet the Author

Russ Eberhart is Associate Dean of Research at Purdue School of Engineering and Technology in Indianapolis, IN. He is the author of Neural Network PC Tools (Academic Press), a leading book in the field of Neural Networks. Among his credits, he is the former President of the IEEE Neural Networks Council.

Yuhui Shi received the Ph.D. degree in electrical engineering from Southeast University, China, in 1992. Since then, he has worked at several universities including the Department of Radio Engineering, Southeast University, Nanjing, China, the Department of Electrical & Computer Engineering, Concordia University, Montreal, Canada, the Department of Computer Science, Australian Defense Force Academic, Canberra, Australia, the Department of Computer Science, Korean Advanced Institute of Science and Technology, Taejon, Korea, and the Department of Electrical Engineering, Purdue School of Engineering and Technology, Indianapolis, Indiana, USA. He is currently with Electronic Data Systems, Inc., Kokomo, Indiana, USA, as an Applied Specialist. His main interests include artificial neural networks, evolutionary computation, fuzzy logic systems and their industrial applications.

Dr. Shi was a co-presenter of the tutorial, Introduction to Computation Intelligence, at the 1998 WCCI Conference, Anchorage, Alaska, and presented the tutorial, Evolutionary Computation and Fuzzy Systems, at the 1998 ANNIE Conference, St. Louis. He is the technical co-chair of 2001 Particle Swarm Optimization Workshop, Indianapolis, Indiana.

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Table of Contents

FOUNDATIONS
COMPUTATIONAL INTELLIGENCE
EVOLUTIONARY COMPUTATION CONCEPTS AND PARADIGMS
EVOLUTIONARY COMPUTATION IMPLEMENTATIONS
NEURAL NETWORK CONCEPTS AND PARADIGMS
NEURAL NETWORK IMPLEMENTATIONS
FUZZY SYSTEMS CONCEPTS AND PARADIGMS
FUZZY SYSTEMS IMPLEMENTATIONS
COMPUTATIONAL INTELLIGENCE IMPLEMENTATIONS
PERFORMANCE METRICS
ANALYSIS AND EXPLANATION
CASE STUDY SUMMARIES

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