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Article

HGA: Hybrid genetic algorithm in fuzzy rule-based classification systems for high-dimensional problems

Applied Soft Computing Journal. 2012. Vol. 12. No. 2. P. 800-806.
Pardalos P. M., Aydogan E., Karaoglan I.
The aim of this work is to propose a hybrid heuristic approach (called hGA) based on genetic algorithm (GA) and integer-programming formulation (IPF) to solve high dimensional classification problems in linguistic fuzzy rule-based classification systems. In this algorithm, each chromosome represents a rule for specified class, GA is used for producing several rules for each class, and finally IPF is used for selection of rules from a pool of rules, which are obtained by GA. The proposed algorithm is experimentally evaluated by the use of non-parametric statistical tests on seventeen classification benchmark data sets. Results of the comparative study.