A new mathematical model for fuzzy cognitive maps-application to medical problems

A. P. Anninou, P. P. Groumpos

Аннотация


The aim of this study is to construct a Medical Decision Support System by using a new evolutionary type of classic Fuzzy Cognitive Map, the one of Dynamic Fuzzy Cognitive Knowledge Network (DFCKN), which is focused on dynamic aspects of the variables. Applications to Medical problems are presented.


Ключевые слова


Modelling; Dynamic Fuzzy Cognitive Knowledge Networks; Fuzzy Cognitive Maps; Meniscus Injuries

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Литература


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Anninou A. P., Groumpos P. P. Non linear Hebbian learning techniques and fuzzy cognitive maps in modeling the Parkinson's disease. In Control & Automation (MED), 2013 21st Mediterranean Conference on 2013, pp. 709-715.

Groumpos P., Gkountroumani V. A New Control Strategy for Modeling Wind Energy Systems Using Fuzzy Cognitive Maps. Journal of Energy and Power Engineering, 8(11).

Mpelogianni V., Groumpos P.P. A revised approach in modeling fuzzy cognitive maps. In Control and Automation (MED), 2016 24th Mediterranean Conference on 2016, pp. 350-354.

Vergini, E., Groumpos P. P. New concerns on fuzzy cognitive maps equation and sigmoid function. In Control and Automation (MED), 2017 25th Mediterranean Conference on 2017, pp. 1113-1118.

A New Approach of Dynamic Fuzzy Cognitive Knowledge Networks in Modelling Diagnosing Process Of Meniscus / A. P. Anninou, et al. In the 20th World Congress of the International Federation of Automatic Control IFAC, Toulouse, France.2017.

Papageorgiou E. I., Stylios C. D., Groumpos P. P. Active Hebbian learning algorithm to train fuzzy cognitive maps. International Journal of Approximate Reasoning, 37. 2004. pp. 219-249.


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(c) 2019 A. P. Anninou, P. P. Groumpos