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Knowledge Processing with Interval and Soft Computing

  • Book
  • © 2008

Overview

Editors:
  1. Vladik Kreinovich

    1. Dept. Computer Science, University of Texas, El Paso, USA

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  2. Andre Korvin

    1. Dept. Computer &, University of Houston-Downtown, Houston, USA

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  3. R. Baker Kearfott

    1. Dept. Mathematics, University of Louisiana, Lafayette , Lafayette, USA

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  4. Chenyi Hu

    1. Computer Science Department, University of Central Arkansas, Conway, USA

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  • Provides necessary theoretical foundations for applying interval and soft computing in artificial intelligence and knowledge processing (AIKP)
  • Includes applicable algorithms that can be used to solve AIKP problems
  • Presents successful applications
  • Includes supplementary material: sn.pub/extras

Part of the book series: Advanced Information and Knowledge Processing (AI&KP)

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Table of contents (10 chapters)

  1. Front Matter

    Pages 1-10
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  2. Fundamentals of Interval Computing

    • Ralph Baker Kearfott, Chenyi Hu
    Pages 1-12

  3. Soft Computing Essentials

    • Andre de Korvin, Hong Lin, Plamen Simeonov
    Pages 13-74

  4. Relations Between Interval Computing and Soft Computing

    • Vladik Kreinovich
    Pages 75-97

  5. Interval Matrices in Knowledge Discovery

    • Chenyi Hu, R. Baker Kearfott
    Pages 99-117

  6. Interval Function Approximation and Applications

    • Chenyi Hu, Ling T He, Shanying Xu
    Pages 119-134

  7. Interval Rule Matrices for Decision Making

    • Chenyi Hu
    Pages 135-146

  8. Interval Matrix Games

    • W. Dwayne Collins, Chenyi Hu
    Pages 147-165

  9. Interval-Weighted Graphs and Flow Networks

    • Chenyi Hu, Ping Hu
    Pages 167-182

  10. Arithmetic on Bounded Families of Distributions A Denv Algorithm Tutorial

    • Daniel Berleant, Gary Anderson, Chaim Goodman-Strauss
    Pages 183-210

  11. IntBox An Object-Oriented Interval Computing Software Toolbox in C++

    • Michael Nooner, Chenyi Hu
    Pages 211-228

  12. Back Matter

    Pages 1-5
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Keywords

About this book

Interval computing combined with fuzzy logic has become an emerging tool in studying artificial intelligence and knowledge processing (AIKP) applications since it models uncertainties frequently raised in the field. This book provides introductions for both interval and fuzzy computing in a very accessible style.

Application algorithms covered in this book include quantitative and qualitative data mining with interval valued datasets, decision making systems with interval valued parameters, interval valued Nash games and interval weighted graphs. Successful applications in studying finance and economics, etc are also included.

This book can serve as a handbook or a text for readers interested in applying interval and soft computing for AIKP.

Editors and Affiliations

  • Dept. Computer Science, University of Texas, El Paso, USA

    Vladik Kreinovich

  • Dept. Computer &, University of Houston-Downtown, Houston, USA

    Andre Korvin

  • Dept. Mathematics, University of Louisiana, Lafayette , Lafayette, USA

    R. Baker Kearfott

  • Computer Science Department, University of Central Arkansas, Conway, USA

    Chenyi Hu

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