Multi-objective optimization of TSK fuzzy models

Authors:
O. Guenounou;A. Belmehdi;B. Dahhou
Affiliations:
Laboratory of Industrial Technology and Information LT2I, University of Bejaia, Route de l'université Targa Ouzemour, Béjaia, Algeria;Laboratory of Industrial Technology and Information LT2I, University of Bejaia, Route de l'université Targa Ouzemour, Béjaia, Algeria;Laboratory for the Analysis and Architecture of Systems LAAS, Toulouse, France
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

In this paper we propose a hybrid algorithm to optimize the structure of TSK type fuzzy model using backpropagation (BP) learning algorithm and non-dominated sorting genetic algorithm (NSGA-II). In a first step, BP algorithm is used to optimize the parameters of the model (parameters of membership functions and fuzzy rules). NSGA-II is used in a second phase, to optimize the number of fuzzy rules and to fine tune the parameters. A well known benchmark is used to evaluate performances of the proposed modelling approach, and compare it with other modelling approaches.