Fuzzy rule-based expert systems and genetic machine learning
Author(s)
Bibliographic Information
Fuzzy rule-based expert systems and genetic machine learning
(Studies in fuzziness and soft computing, 3)
Physica-Verlag, c1997
Second, revised and enlarged ed
Available at 18 libraries
  Aomori
  Iwate
  Miyagi
  Akita
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  Fukushima
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  Niigata
  Toyama
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  Fukui
  Yamanashi
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  Aichi
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  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
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  Tokushima
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  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
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Note
Includes bibliographical references (p. [379]-410) and index
Description and Table of Contents
Description
This work presents fuzzy rule-languages as links between quantitative and qualitative models. In the first part, the semantic of fuzzy rule-languages is extended with a type system and an object-oriented system. In the second part, fuzzy rule-languages are integrated with genetic algorithms and with classifier systems. For this purpose, the class of genetic algorithms over context-free languages has been developed.
Table of Contents
Contents: Fuzzy Rule-Based Expert Systems: Fuzzy Technologies.- Introduction to Fuzzy Sets.- Natural Language Computation.- A Little but Extendible Language.- Hybrid Reasoning.- A Fuzzy Backtrack Algorithm.- Fuzzy Classifier Systems: Genetic Algorithms.- The Genetic Machinery over Context-Free Languages.- Fuzzy Classifier Systems.- The Monte Carlo Selection Rule.- The Search Space Size of Fuzzy Classifier Systems.
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