Fuzzy if ... then rule models and their transformation into one another

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Abstract

The two most essential fuzzy rule-based models used in the literature and in the industrial applications are briefly described. The way of reasoning in these models is shown. Interpolative reasoning for the case of sparse rule bases is also discussed. Rule base compression by eliminating redundant rules whose information can be reconstructed within a set accuracy interval from the remaining rules by using the previous interpolation method is shown. A general fuzzy model is discussed that contains the previous fuzzy models (as well as the nonfuzzy one) as special cases. Ways of transforming the different approximative models into each other via the general model and interpolation are presented.

Original languageEnglish
Pages (from-to)621-637
Number of pages17
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
Volume26
Issue number5
DOIs
Publication statusPublished - 1996

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Fuzzy If-then Rules
Rule Base
Fuzzy Model
Reasoning
Interpolation
Interpolation Method
Industrial Application
Fuzzy Rules
Model
Compression
Interpolate
Fuzzy rules
Industrial applications
Interval

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Theoretical Computer Science
  • Computational Theory and Mathematics

Cite this

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