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PROJECT TITLE :

A New Fuzzy Cognitive Map Structure Based on the Weighted Power Mean

ABSTRACT:

We tend to introduce a new structure for fuzzy cognitive maps (FCM) where the ancient fan-in structure involving an inner product followed by a squashing function to describe the causal influences of antecedent nodes to a specific consequent node is replaced with a weighted mean type operator. During this paper, we use the weighted power mean (WPM). Through acceptable choice of the weights and exponents in the WPM operators, we have a tendency to will both account for the relative importance of different antecedent nodes in the dynamics of a particular node, also take a perspective ranging continuously from the foremost pessimistic (minimum) to the foremost optimistic (most) on the normalized aggregation of antecedents for every node. We think about this FCM structure to be more intuitive than the traditional one, as the nonlinearity concerned within the WPM is more scrutable with regard to the aggregation of its inputs. We offer examples of this new FCM structure to illustrate its behavior, including its convergence, and compare it with a ancient FCM architecture on a situation presented in previous works.


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