Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

J. Botzheim, C. Cabrita, L. 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 publicationIEEE International Conference on Fuzzy Systems
Pages1667-1672
Number of pages6
Volume3
DOIs
Publication statusPublished - 2004
Event2004 IEEE International Conference on Fuzzy Systems - Proceedings - Budapest, Hungary
Duration: Jul 25 2004Jul 29 2004

Other

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

Fingerprint

Membership functions
Fuzzy rules
Fuzzy systems
Identification (control systems)

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

Cite this

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

Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm. / Botzheim, J.; Cabrita, C.; Kóczy, L.; Ruano, A. E.

IEEE International Conference on Fuzzy Systems. Vol. 3 2004. p. 1667-1672.

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

Botzheim, J, Cabrita, C, Kóczy, L & Ruano, AE 2004, Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm. in IEEE International Conference on Fuzzy Systems. vol. 3, pp. 1667-1672, 2004 IEEE International Conference on Fuzzy Systems - Proceedings, Budapest, Hungary, 7/25/04. https://doi.org/10.1109/FUZZY.2004.1375431
Botzheim J, Cabrita C, Kóczy L, Ruano AE. Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm. In IEEE International Conference on Fuzzy Systems. Vol. 3. 2004. p. 1667-1672 https://doi.org/10.1109/FUZZY.2004.1375431
Botzheim, J. ; Cabrita, C. ; Kóczy, L. ; Ruano, A. E. / Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm. IEEE International Conference on Fuzzy Systems. Vol. 3 2004. pp. 1667-1672
@inproceedings{e5c97f0682184effb3860e5f99d73e4f,
title = "Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm",
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.",
author = "J. Botzheim and C. Cabrita and L. K{\'o}czy and Ruano, {A. E.}",
year = "2004",
doi = "10.1109/FUZZY.2004.1375431",
language = "English",
isbn = "0780383532",
volume = "3",
pages = "1667--1672",
booktitle = "IEEE International Conference on Fuzzy Systems",

}

TY - GEN

T1 - Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

AU - Botzheim, J.

AU - Cabrita, C.

AU - Kóczy, L.

AU - Ruano, A. E.

PY - 2004

Y1 - 2004

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=11144340459&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=11144340459&partnerID=8YFLogxK

U2 - 10.1109/FUZZY.2004.1375431

DO - 10.1109/FUZZY.2004.1375431

M3 - Conference contribution

SN - 0780383532

VL - 3

SP - 1667

EP - 1672

BT - IEEE International Conference on Fuzzy Systems

ER -