Knowledge Processing with Interval and Soft Computing (Advanced Information and Knowledge Processing)

✍ Scribed by Chenyi Hu (editor), R. Baker Kearfott (editor), Andre de Korvin (editor), Vladik Kreinovich (editor)

Publisher: Springer
Year: 2008
Tongue: English
Leaves: 241
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Preface
List of Contributors
1 Fundamentals of Interval Computing
Ralph Baker Kearfott, Chenyi Hu
2 Soft Computing Essentials
Andre de Korvin, Hong Lin, and Plamen Simeonov
3 Relations Between Interval Computing and Soft Computing
Vladik Kreinovich
4 Interval Matrices in Knowledge Discovery
Chenyi Hu, R. Baker Kearfott
5 Interval Function Approximation and Applications
Chenyi Hu, Ling T. He, Shanying Xu
6 Interval Rule Matrices for Decision Making
Chenyi Hu
7 Interval Matrix Games
W. Dwayne Collins, Chenyi Hu
8 Interval-Weighted Graphs and Flow Networks
Chenyi Hu, Ping Hu
9 Arithmetic on Bounded Families of Distributions: A DEnv Algorithm Tutorial
Daniel Berleant, Gary Anderson, Chaim Goodman-Strauss
10 IntBox: An Object-Oriented Interval Computing Software Toolbox in C++
Michael Nooner, Chenyi Hu
Index

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