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Practical Applications of Computational Intelligence Techniques

  • Lakhmi Jain
  • Philippe De Wilde

Part of the International Series in Intelligent Technologies book series (ISIT, volume 16)

Table of contents

  1. Front Matter
    Pages i-xv
  2. N. Magnenat-Thalmann, C. Joslin, U. Berner
    Pages 65-88
  3. J. M. Moreno, J. Madrenas, J. Cabestany
    Pages 89-120
  4. M. Mraz, N. Zimic, I. Lapanja, J. Virant, B. Skrt
    Pages 121-145
  5. W. D. Potter, W. Bi, D. Twardus, H. Thistle, M. J. Twery, J. Ghent et al.
    Pages 177-222
  6. M. Sordo, H. Buxton, D. Watson
    Pages 299-330
  7. Back Matter
    Pages 379-381

About this book

Introduction

Computational intelligence paradigms have attracted the growing interest of researchers, scientists, engineers and application engineers in a number of everyday applications. These applications are not limited to any particular field and include engineering, business, banking and consumer electronics. Computational intelligence paradigms include artificial intelligence, artificial neural networks, fuzzy systems and evolutionary computing. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimisation applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge.
Practical Applications of Computational Intelligence Techniques contains twelve chapters providing actual application of these techniques in the real world. Such examples include, but are not limited to, intelligent household appliances, aerial spray models, industrial applications and medical diagnostics and practice. This book will be useful to researchers, practicing engineers/scientists and students, who are interested in developing practical applications in a computational intelligence environment.

Keywords

algorithms artificial intelligence artificial neural network classification computational intelligence electronics evolution evolutionary computation fuzzy genetic algorithm genetic algorithms knowledge neural network optimization programming

Editors and affiliations

  • Lakhmi Jain
    • 1
  • Philippe De Wilde
    • 2
  1. 1.University of South AustraliaAdelaideAustralia
  2. 2.University of LondonLondonUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-010-0678-1
  • Copyright Information Kluwer Academic Publishers 2001
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-3868-3
  • Online ISBN 978-94-010-0678-1
  • Series Print ISSN 1382-3434
  • Buy this book on publisher's site
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