期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2016
卷号：10
期号：3
页码：9-28
DOI：10.14257/ijseia.2016.10.3.02
出版社：SERSC
摘要：In pattern recognition, clustering is a powerful technique that can be used to find the identical group of objects from a given dataset. It has proven its importance in various domains such as bioinformatics, machine learning, pattern recognition, document clustering and so on. But, in clustering, it is difficult to determine the optimal cluster centers in a given set of data. So, in this paper, a new method called magnetic charged system search (MCSS) is applied to determine the optimal cluster centers. This method based on the behavior of charged particles. The proposed method employs the electric force and magnetic force to initiate the local search while Newton second law of motion is employed for global search. The performance of the proposed algorithm is tested on several datasets which are taken from UCI repository and compared with the other existing methods like K-Means, GA, PSO, ACO and CSS. The experimental results prove the applicability of the proposed method in clustering domain.
关键词：Clustering; charged particles; electric force; magnetic force; Newton Law
