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Scheduling exploration/exploitation levels in genetically-generated fuzzy knowledge bases

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3 Author(s)
Achiche, S. ; Dept. of Mech. Eng., Ecole Polytech. de Montreal, Que., Canada ; Baron, L. ; Balazinski, M.

In this paper we study the influence of the exploration/exploitation balance on the performances of a real binary/like coded genetic algorithm in automatically generating fuzzy knowledge bases from a set of numerical data. The influence is explored through different scheduling of crossover strategies throughout the evolution process. The aim is to prove the influence of a good balance between exploration and exploitation levels on the performances of the optimization algorithm, along with the influence of a good definition of the early versus late stages of the evolution.

Published in:

Fuzzy Information, 2004. Processing NAFIPS '04. IEEE Annual Meeting of the  (Volume:1 )

Date of Conference:

27-30 June 2004