Multi-Objective Genetic Fuzzy Systems: On the Necessity of Including Expert Knowledge in the MOEA Design Process

M. J. Gacto, R. Alcalá and F. Herrera

This work analyzes the application of Multi-Objective Evolutionary Algorithms in order to attain the desired accuracy/interpretability balance of Fuzzy Rule-Based Systems by preserving the improved accuracy that a tuning of membership functions could give and obtaining more compact models. The results shows that the use of expert knowledge in the algorithm design process can significantly improve the search ability of these algorithms, obtaining more accurate and at the same time simpler models with respect to the single objective based approach.

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