Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

J. Botzheim, C. Cabrita, L. T. Kóczy, A. E. Ruano

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

17 Citations (Scopus)

Abstract

In previous papers from the authors fuzzy model identification methods were discussed. The bacterial algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt algorithm was also proposed for determining membership functions in fuzzy systems. In this paper the Levenberg-Marquardt technique is improved to optimise the membership functions in the fuzzy rules without Ruspini-partition. 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 functions as well.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Fuzzy Systems - Proceedings
Pages1667-1672
Number of pages6
DOIs
Publication statusPublished - Dec 1 2004
Event2004 IEEE International Conference on Fuzzy Systems - Proceedings - Budapest, Hungary
Duration: Jul 25 2004Jul 29 2004

Publication series

NameIEEE International Conference on Fuzzy Systems
Volume3
ISSN (Print)1098-7584

Other

Other2004 IEEE International Conference on Fuzzy Systems - Proceedings
CountryHungary
CityBudapest
Period7/25/047/29/04

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ASJC Scopus subject areas

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

Cite this

Botzheim, J., Cabrita, C., Kóczy, L. T., & Ruano, A. E. (2004). Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm. In 2004 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 1667-1672). (IEEE International Conference on Fuzzy Systems; Vol. 3). https://doi.org/10.1109/FUZZY.2004.1375431