A first study of fuzzy cognitive maps learning using particle swarm optimization

We introduce a new algorithm for fuzzy cognitive maps learning. The proposed approach is based on the particle swarm optimization method and it is used for the detection of proper weight matrices that lead the fuzzy cognitive map to desired steady states. For this purpose a properly defined objective function that incorporates experts' knowledge is constructed and minimized. The application of the proposed methodology to an industrial control problem supports the claim that the proposed technique is efficient and robust.

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