期刊名称：International Journal of Mechatronics, Electrical and Computer Technology
印刷版ISSN：2305-0543
出版年度：2015
卷号：5
期号：15
页码：2198-2206
出版社：Austrian E-Journals of Universal Scientific Organization
摘要：In this paper we compare parallel grouping genetic algorithm with serial grouping genetic algorithm for data clustering. According to our experimental results, the proposed parallel grouping genetic algorithm (PGGA) considerably decreases the CPU time without inversely influence on the answer
