Extension of the Levenberg-Marquardt algorithm for the extraction of trapezoidal and general piecewise linear fuzzy rules

J. Botzheim, L. T. Kóczy, A. E. Ruano

Research output: Contribution to journalConference article

5 Citations (Scopus)

Abstract

This paper discusses how training algorithms for determining membership functions in fuzzy rule based systems can be applied. There are several training algorithms, which have been developed initially for neural networks and can be adapted to fuzzy systems. In this paper the Levenberg-Marquardt algorithm is introduced, allowing the determination of an optimal rule base and converging faster than some more classic methods (e.g. the standard Back Propagation algorithm). The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear function as well.

Original languageEnglish
Pages (from-to)815-819
Number of pages5
JournalIEEE International Conference on Fuzzy Systems
Volume1
Publication statusPublished - Dec 31 2002
Event2002 IEEE International Conference on Fuzzy Systems: FUZZ-IEEE'02 - Honolulu, HI, United States
Duration: May 12 2002May 17 2002

ASJC Scopus subject areas

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

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