A flexible nonlinear approach to represent cause-effect relationships in FCMs

Maria K. Ketipi, Dimitrios E. Koulouriotis, Evangelos G. Karakasis, George A. Papakostas, Vassilios D. Tourassis

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Fuzzy Cognitive Maps is an important representation tool that has the ability to model complicated systems. Based on linear influence relations between concepts, FCMs can be trained to lead a system to a desired state. This work proposes a generalized flexible nonlinear function as an alternative way of estimating that influence. Its adjustable character offers the ability to lead a FCM into a large set of different equilibrium states, where the conventional approach constitutes only one instance. Experimental studies present the properties of the proposed methodology in two benchmarks and other synthetic data. The examination of a system under different considerations of influence offers a more complete understanding of a system behavior.

Original languageEnglish
Pages (from-to)3757-3770
Number of pages14
JournalApplied Soft Computing Journal
Issue number12
Publication statusPublished - Dec 1 2012


  • Fuzzy Cognitive Maps
  • Generalized logistic function
  • Influence
  • Nonlinear function

ASJC Scopus subject areas

  • Software

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