Stability of Fixed-Point Values in Reduced Fuzzy Cognitive Map Models

Miklós F. Hatwágner, László T. Kóczy

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The authors have already presented their method for reducing oversized FCM models, and also have analyzed the prediction error of the reduced models. These investigations assumed that models have a single fixed-point attractor. The novelty of this paper is that it deals with the stability behavior of the fixed-point attractor value of original-reduced model pairs and compares the number of fixed-point attractors found, the asymptotic values of the concepts, and also checks if any limit cycles or chaotic behavior occur. The method of comparison and also the first results made with two real-life and one synthetic model are presented and some conclusions are taken.

Original languageEnglish
Title of host publicationStudies in Fuzziness and Soft Computing
PublisherSpringer
Pages359-372
Number of pages14
DOIs
Publication statusPublished - 2021

Publication series

NameStudies in Fuzziness and Soft Computing
Volume393
ISSN (Print)1434-9922
ISSN (Electronic)1860-0808

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mathematics

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    Hatwágner, M. F., & Kóczy, L. T. (2021). Stability of Fixed-Point Values in Reduced Fuzzy Cognitive Map Models. In Studies in Fuzziness and Soft Computing (pp. 359-372). (Studies in Fuzziness and Soft Computing; Vol. 393). Springer. https://doi.org/10.1007/978-3-030-47124-8_29