Improving a Fuzzy Inference System by Means of Evolution Strategy

In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system (FIS). The presented approach additionally serves as a method to predetermine the structure of radial basis function networks (RBFN): the number of hidden units as well as the starting parameters for a further optimization are estimated.