Simplification of fuzzy rule based systems using orthogonal transformation

John Yen, Liang Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

It is known that removal of those redundant fuzzy rules from a rule base can result in a more compact fuzzy model with better generalizing ability. In this paper we propose a number of orthogonal transformation based methods which provide new or alternative tools for rule extraction. A common attribute of these methods is that they all work on a truth value matrix and employ some measure index to detect the rules that should be retained and eliminated. The performance of these methods is illustrated using a nonlinear plant modeling example.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Fuzzy Systems
PublisherIEEE
Pages253-258
Number of pages6
Volume1
StatePublished - 1997
EventProceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) - Barcelona, Spain
Duration: Jul 1 1997Jul 5 1997

Other

OtherProceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)
CityBarcelona, Spain
Period7/1/977/5/97

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

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  • Cite this

    Yen, J., & Wang, L. (1997). Simplification of fuzzy rule based systems using orthogonal transformation. In IEEE International Conference on Fuzzy Systems (Vol. 1, pp. 253-258). IEEE.