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共进化模糊建模Coevolutionary Fuzzy Modeling

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共进化模糊建模Coevolutionary Fuzzy Modeling

最 低 价：￥366.10

定 价：￥406.80

作 者：CarlosAndrés Peña-Reyes 著

出 版 社：Oversea Publishing House

出版时间：2004-11-23

I S B N：9783540229940

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    内容简介
    Building on fuzzy logic and evolutionary computing, this book introduces fuzzy cooperative coevolution as a novel approach to systems design, conductive to explaining human decision process. Fuzzy cooperative coevolution is a methodology for constructing systems able to accurately predict the outcome of a decision-making process, while providing an understandable explanation of the underlying reasoning.
    　　The central contribution of this work is the use of an advanced evolutionary technique, cooperative coevolution, for dealing with the simultaneous design of connective and operational parameters. Cooperative coevolution overcomes several limitations exhibited by other standard evolutionary approaches.
    　　The applicability of fuzzy cooperative coevolution is validated by modeling the decision processes of three real-world problems, an iris data benchmark problem and two problems from breast cancer diagnosis.

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    目录
    1　Introductio
    　1.1 General Context
    　1.1.1 Problem De
    　1.1.2 Propsed Solution
    　1.1.3 Outing of the book
    　1.2 Fuzzy Systems
    　 1.2.1 Basic Notions fo Fuzzy Stes and Fuzzy Logic
    　 1.2.2 Conditional Fuzzy Statements
    　 1.2.3 Fuzzy Interence
    　1.2.4 Fuzzy Inference Systems
    　1.3 Evolutionary Computaition
    　 1.3.1 Genetic Algorithms
    　 1.3.2 Gendtic Programming
    　 1.3.3 evolution Strategies
    　 1.3.4 Evolutionary Programming
    　 1.3.5 Classifier Systems
    2 evolutionary Fuzzy Modeling
    2.1 Fuzzy Modeling: the Art of Building Fuzzy Systems
    2.1.1 The Fuzzy Modeling Problem
    2.1.2 Approaches and thechniques
    2.2 Evolutionary Fuzzy Modeling
    2.2.1 Applying Eovolution to Fuzzy Modeling
    2.2.2 Three Approaches to Behavior and Sructure Learning
    2.3 Interpretability Considerations
    2.3.1 Semantic Criteria
    2.3.2 Syntactic Criteria
    2.3.3 Strategies to Satisfy Semantic and Syntactic Criteria
    2.4 Example:Medical Diagnosis
    2.4.1 The Wisconsin breast Cancer Diagnosis(WBCD)Problem
    2.4.2 A Genetic-Fuzzy Approach to the WBCDProblem
    2.4.3 Rsults
    2.4.4 Diagnostic Confidence
    2.4.5 further Experiments
    3 Coevolutionary Fuzzy Modeling
    4 Breast Cancer Diagnosis by Fuzzy CoCo
    5 Analyzing Fuzzy CoCo
    6 Extensions of the Methobology
    BIbliography

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