Parameterization and concept optimization of FCM models

Miklos F. Hatwagner, L. Kóczy

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

8 Citations (Scopus)

Abstract

Fuzzy Cognitive Maps (FCM) are widely used to model and analyze the behavior of complex multicomponent systems. The application of FCM might be non-trivial in some specific context, however. Two rather general problems of the application of FCM and respective solutions are described in this paper. The first problem is as follows: In some cases the concept values obtained at the end of an FCM simulation are very similar. If this occurs, the order of concepts, thus their relative importance cannot well defined. The second problem is to select the appropriate concepts and to define their number. The concepts are given by human experts, but the selection of the appropriate concepts which help to reach the required accuracy of the model, while keeping the model as simple as possible is a difficult task. This paper deals with these two (connected) problems and proposes solutions for them. The proposed solution for the first problem is to choose the optimal λ parameter value in the threshold function, the one for the second is to apply a 'state reduction method' based on fuzzy tolerance relations presented in the paper.

Original languageEnglish
Title of host publicationFUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2015-November
ISBN (Electronic)9781467374286
DOIs
Publication statusPublished - Nov 25 2015
EventIEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 - Istanbul, Turkey
Duration: Aug 2 2015Aug 5 2015

Other

OtherIEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015
CountryTurkey
CityIstanbul
Period8/2/158/5/15

Fingerprint

Fuzzy Cognitive Maps
Parameterization
Optimization
Tolerance Relation
Multicomponent Systems
Threshold Function
Model
Fuzzy Relation
Large scale systems
Optimal Parameter
Reduction Method
Well-defined
Complex Systems
Choose
Concepts
Simulation

Keywords

  • Fuzzy Cognitive Maps
  • parameter optimization
  • state reduction

ASJC Scopus subject areas

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

Cite this

Hatwagner, M. F., & Kóczy, L. (2015). Parameterization and concept optimization of FCM models. In FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems (Vol. 2015-November). [7337888] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2015.7337888

Parameterization and concept optimization of FCM models. / Hatwagner, Miklos F.; Kóczy, L.

FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. 7337888.

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

Hatwagner, MF & Kóczy, L 2015, Parameterization and concept optimization of FCM models. in FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. vol. 2015-November, 7337888, Institute of Electrical and Electronics Engineers Inc., IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, Istanbul, Turkey, 8/2/15. https://doi.org/10.1109/FUZZ-IEEE.2015.7337888
Hatwagner MF, Kóczy L. Parameterization and concept optimization of FCM models. In FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. Vol. 2015-November. Institute of Electrical and Electronics Engineers Inc. 2015. 7337888 https://doi.org/10.1109/FUZZ-IEEE.2015.7337888
Hatwagner, Miklos F. ; Kóczy, L. / Parameterization and concept optimization of FCM models. FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015.
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