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© 2010

Tree-Structure based Hybrid Computational Intelligence

Theoretical Foundations and Applications

  • Covering the new field of Flexible Neural Trees Networks in a well structured way

  • The state of the art of Flexible Neural Trees networks for researchers and graduate students

Book

Part of the Intelligent Systems Reference Library book series (ISRL, volume 2)

Table of contents

  1. Front Matter
  2. Foundations of Computational Intelligence

    1. Front Matter
      Pages 1-1
    2. Yuehui Chen, Ajith Abraham
      Pages 3-36
  3. Flexible Neural Trees

    1. Front Matter
      Pages 37-37
    2. Yuehui Chen, Ajith Abraham
      Pages 39-96
  4. Hierarchical Neural Networks

    1. Front Matter
      Pages 97-97
    2. Yuehui Chen, Ajith Abraham
      Pages 99-125
  5. Hierarchical Fuzzy Systems

    1. Front Matter
      Pages 127-127
    2. Yuehui Chen, Ajith Abraham
      Pages 129-147
  6. Reverse Engineering of Dynamical Systems

    1. Front Matter
      Pages 149-149
    2. Yuehui Chen, Ajith Abraham
      Pages 151-182
  7. Conclusions and Future Research

    1. Front Matter
      Pages 183-183
    2. Yuehui Chen, Ajith Abraham
      Pages 185-190
  8. Back Matter

About this book

Introduction

Research in computational intelligence is directed toward building thinking machines and improving our understanding of intelligence. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. In this book, the authors illustrate an hybrid computational intelligence framework and it applications for various problem solving tasks. Based on tree-structure based encoding and the specific function operators, the models can be flexibly constructed and evolved by using simple computational intelligence techniques. The main idea behind this model is the flexible neural tree, which is very adaptive, accurate and efficient. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved.

This volume comprises of 6 chapters including an introductory chapter giving the fundamental definitions and the last Chapter provides some important research challenges. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques and data mining will find the comprehensive coverage of this book invaluable.

Keywords

cognition computational intelligence data mining dynamical systems emotion fuzzy system learning neural network problem solving proving

Authors and affiliations

  1. 1.School of Information Science and EngineeringUniversity of Jinan JinanP.R. China
  2. 2.Machine Intelligence Research Labs (MIR Labs)Scientific Network for Innovation and Research Excellence AuburnUSA

Bibliographic information

  • Book Title Tree-Structure based Hybrid Computational Intelligence
  • Book Subtitle Theoretical Foundations and Applications
  • Authors Yuehui Chen
    Ajith Abraham
  • Series Title Intelligent Systems Reference Library
  • DOI https://doi.org/10.1007/978-3-642-04739-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-642-04738-1
  • Softcover ISBN 978-3-642-26120-6
  • eBook ISBN 978-3-642-04739-8
  • Series ISSN 1868-4394
  • Series E-ISSN 1868-4408
  • Edition Number 1
  • Number of Pages XIV, 206
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Artificial Intelligence
    Computational Intelligence
  • Buy this book on publisher's site
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Reviews

From the reviews:

“The book puts forward a hierarchical hybrid computational intelligence framework, in which models of a hierarchical structure and appropriate types of function operators are created and optimized by means of computational intelligence techniques. … The book is both informative and stimulating and thus becomes an interesting and valuable source.” (Ruxandra Stoean, Zentralblatt MATH, Vol. 1195, 2010)