A novel chemistry based metaheuristic optimization method for mining of classification rules

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摘要

When investigated carefully, chemical reactions possess efficient objects, states, process, and events that can be designed as a computational method en bloc. In this study, a novel computational method, which is robust and have less parameters than that of used in the literature, is intended to be developed inspiring from types and occurring of chemical reactions. The proposed method is named as artificial chemical reaction optimization algorithm, ACROA. In this study, one of the first applications of this method has been performed in classification rule discovery field of data mining and efficiency has been demonstrated.

论文关键词:Artificial chemical reaction optimization algorithm,Data mining,Classification rules,Heuristic optimization,Performance,Uniform population

论文评审过程:Available online 1 April 2012.

论文官网地址:https://doi.org/10.1016/j.eswa.2012.03.066