On the Convergence of Sigmoidal Fuzzy Grey Cognitive Maps
| Autor: | István Á. Harmati, László T. Kóczy |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Cognitive map Computer science Applied Mathematics fuzzy grey cognitive map 02 engineering and technology Sigmoid function fuzzy cognitive map QA75.5-76.95 Fuzzy logic 020901 industrial engineering & automation fixed point Electronic computers. Computer science Convergence (routing) 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) QA1-939 Applied mathematics 020201 artificial intelligence & image processing grey system theory Engineering (miscellaneous) Mathematics |
| Zdroj: | International Journal of Applied Mathematics and Computer Science, Vol 29, Iss 3, Pp 453-466 (2019) |
| ISSN: | 2083-8492 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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