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Soft Computing and Human-Centered Machines

Author: Zhi-Qiang Liu; Sadaaki Miyamoto
Publisher: Tokyo : Springer Japan, 2000.
Series: Computer science workbench.
Edition/Format:   eBook : Bibliographic data : EnglishView all editions and formats
Summary:
Today's networked world and the decentralization that the Web enables and symbolizes have created new phenomena: information explosion and saturation. To deal with information overload, our computers should have human-centered functionality and enhanced intelligence, but instead they simply become faster. Soft computing is a unifying framework that combines techniques in neural networks, fuzzy theory, genetic  Read more...
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Details

Genre/Form: Electronic books
Material Type: Bibliographic data, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Zhi-Qiang Liu; Sadaaki Miyamoto
ISBN: 9784431679073 4431679073
OCLC Number: 840303192
Description: 1 online resource (XVIII, 327 pages 95 illustrations).
Contents: Introduction --
Multisets and Fuzzy Multisets --
Model Logic, Rough Sets, and Fuzzy Sets --
Fuzzy Cognitive Maps: Analysis and Extensions --
Methods in Hard and Fuzzy Clustering --
Soft-Competitive Learning Paradigms --
Aggregation Operations for Fusing Fuzzy Information --
Fuzzy Gated Neural Networks in Pattern Recognition --
Soft Computing Technique in Kansei (Emotional) Information Processing --
Vagueness in Human Judgment and Decision Making --
Chaos and Time Series Analysis --
A Short Course for Fuzzy Set Theory.
Series Title: Computer science workbench.
Responsibility: edited by Zhi-Qiang Liu, Sadaaki Miyamoto.

Abstract:

Today's networked world and the decentralization that the Web enables and symbolizes have created new phenomena: information explosion and saturation. To deal with information overload, our computers should have human-centered functionality and enhanced intelligence, but instead they simply become faster. Soft computing is a unifying framework that combines techniques in neural networks, fuzzy theory, genetic algorithms, and artificial intelligence to develop intelligent systems able to learn in dynamic, imprecise, and uncertain environments. This book explains the theory, methodology, and application aspects of human-centered systems, showing how it is possible to extend to machines such techniques as dynamic cognitive learning, neural-fuzzy-based learning, and genetic-evolutionary type learning paradigms.

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