SIFT-SS: an advanced steady-state multi-objective genetic fuzzy system

Authors:
Michel González;Jorge Casillas;Carlos Morell
Affiliations:
Universidad Central “Marta Abreu” de Las Villas, CUBA;Dept Computer Science and Artificial Intelligence, University of Granada, Spain;Universidad Central “Marta Abreu” de Las Villas, CUBA
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Year:
2010

Citing 4
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Abstract

Nowadays, automatic learning of fuzzy rule-based systems is being addressed as a multi-objective optimization problem A new research area of multi-objective genetic fuzzy systems (MOGFS) has capture the attention of the fuzzy community Despite the good results obtained, most of existent MOGFS are based on a gross usage of the classic multi-objective algorithms This paper takes an existent MOGFS and improves its convergence by modifying the underlying genetic algorithm The new algorithm is tested in a set of real-world regression problems with successful results.