Initialization method for fuzzy Takagi–Sugeno systems

Resumo

This paper presents a method for initializing Takagi–Sugeno fuzzy systems in which the initial values of fuzzy antecedents are obtained by dynamic decomposition of the input space while the consequent values are obtained by the recursive least squares method. The results of experiments on 13 datasets from the KEEL repository are described. The results of approximating these datasets by the proposed method are compared with those obtained by five well-known identification algorithms..