Weighted fuzzy genetic programming algorithm for structure and parameters selection of fuzzy systems for nonlinear modelling

Abstract

In this paper a weighted fuzzy genetic programming algorithm for selection of structure and parameters of fuzzy systems for nonlinear modelling is proposed. This method is based on fuzzy genetic programming and innovations in this method concern, among the others, using weights of fuzzy aggregation operators, using weights of fuzzy rules, using fitness function criteria designed for fuzzy genetic programming and using dynamic links between fuzzy rules and fuzzy rules base. The proposed method was tested with use of typical nonlinear modelling problems.