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Fuzzy Logic Foundations and Industrial Applications

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Cover of 'Fuzzy Logic Foundations and Industrial Applications'

Table of Contents

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    Book Overview
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    Chapter 1 A Unified View of Case Based Reasoning and Fuzzy Modeling
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    Chapter 2 Open-Mindedness and Probabilities Versus Possibilities
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    Chapter 3 Fuzzy Derivatives and Fuzzy Cauchy Problems Using LP Metric
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    Chapter 4 On the Classification and the Dependencies of the Ordering Methods
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    Chapter 5 Possibility Model and its Applications
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    Chapter 6 Interactive Fuzzy Programming for Multiobjective 0–1 Programming Problems Through Genetic Algorithms with Double Strings
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    Chapter 7 The Handling of Fuzzy Objective Functions in (Multicriteria) Linear Programs
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    Chapter 8 Making Decisions on Fuzzy Integer Linear Programming Problems
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    Chapter 9 Information Diffusion Principle and Application in Fuzzy Neuron
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    Chapter 10 Some Application Examples of Fuzzy Set Theory
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    Chapter 11 Recent Successful Fuzzy Logic Applications in Industrial Automation
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    Chapter 12 FIPS—Foundations of a New Tool for Process Control Problems
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    Chapter 13 Industrial Applications of Fuzzy Logic and Neural Networks in China
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    Chapter 14 The Potential of Fuzzy Logic Applications in Industry
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    Chapter 15 Fuzzy Logic Applications in Nuclear Industry
Attention for Chapter 13: Industrial Applications of Fuzzy Logic and Neural Networks in China
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Chapter title
Industrial Applications of Fuzzy Logic and Neural Networks in China
Chapter number 13
Book title
Fuzzy Logic Foundations and Industrial Applications
Published by
Springer, Boston, MA, January 1996
DOI 10.1007/978-1-4613-1441-7_13
Book ISBNs
978-1-4612-8627-1, 978-1-4613-1441-7
Authors

Xiaozhong Li, Li, Xiaozhong

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