Learning of Type-2 Fuzzy Logic Systems by Simulated Annealing with Adaptive Step Size

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Abstract

In this paper, a combination of an interval type-2 fuzzy logic system (IT2FLS) models and simulated annealing is used to predict the Mackey–Glass time series by searching for the best configuration of the IT2FLS. Simulated annealing is used to learn the parameters of the antecedent and the consequent parts of the rules for a Mamdani model. Simulated annealing is combined with a method to reduce the computations associated with it using adaptive step sizes. The results of the proposed methods are compared to results of a type-1 fuzzy logic system (T1FLS).