Why Fuzzy Cognitive Maps Are Efficient | Zendy

Владик Крейнович | Zendy; Chrysostomos Stylios | Zendy

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Why Fuzzy Cognitive Maps Are Efficient

Author(s) -

Владик Крейнович,

Chrysostomos Stylios

Publication year - 2015

Publication title -

international journal of computers communications and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.422

H-Index - 33

eISSN - 1841-9844

pISSN - 1841-9836

DOI - 10.15837/ijccc.2015.6.2073

Subject(s) - fuzzy cognitive map , relation (database) , computer science , cognition , fuzzy logic , artificial intelligence , artificial neural network , empirical research , machine learning , fuzzy set , data mining , mathematics , fuzzy classification , psychology , statistics , neuroscience

In many practical situations, the relation between the experts’ degrees of confidence in different related statements is well described by Fuzzy Cognitive Maps (FCM). This empirical success is somewhat puzzling, since from the mathematical viewpoint, each FCM relation corresponds to a simplified one-neuron neural network, and it is well known that to adequately describe relations, we need multiple neurons. In this paper, we show that the empirical success of FCM can be explained if we take into account that human’s subjective opinions follow Miller’s seven plus minus two law.

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