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On the Convergence of Sigmoidal Fuzzy Grey Cognitive Maps Cover
Open Access
|Sep 2019

Abstract

Fuzzy cognitive maps (FCMs) are recurrent neural networks applied for modelling complex systems using weighted causal relations. In FCM-based decision-making, the inference about the modelled system is provided by the behaviour of an iteration. Fuzzy grey cognitive maps (FGCMs) are extensions of fuzzy cognitive maps, applying uncertain weights between the concepts. This uncertainty is expressed by the so-called grey numbers. Similarly as in FCMs, the inference is determined by an iteration process which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also turn up. In this paper, based on the grey connections between the concepts and the parameters of the sigmoid threshold function, we give sufficient conditions for the existence and uniqueness of fixed points of sigmoid FGCMs.

DOI: https://doi.org/10.2478/amcs-2019-0033 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 453 - 466
Submitted on: Oct 19, 2018
Accepted on: Apr 6, 2019
Published on: Sep 28, 2019
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 István Á. Harmati, László T. Kóczy, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.