Takagi-Sugeno fuzzy systems structure identification based on piecewise linear initialization

A new method is proposed for structure identification of Takagi-Sugeno fuzzy systems, which is called piecewise linear initialization (PLI). This method is based on clustering of input data and has only one parameter: mean-square deviation of a hyperplane in the cluster from data. Each cluster is a particular rule of the fuzzy system. Based on the cluster are constructed Gaussian membership functions, otherwise consequents of fuzzy rules are constructed using the recursive least square method. The proposed method is compared with other methods by analyzing the mean-square error and the average number of rules on various datasets from the KEEL repository.