文章基本信息

标题：Analyzing and Optimizing ANT-Clustering Algorithm by Using Numerical Methods for Efficient Data Mining
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作者：Md. Asikur Rahman ; Md. Mustafizur Rahman ; Md. Mustafa Kamal Bhuiyan 等
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2012
卷号：2
期号：5
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Clustering analysis is an important function of data mining. There are various clustering methods in Data Mining. Based on these methods various clustering algorithms are developed. Ant-clustering algorithm is one of such approaches that perform cluster analysis based on “Swarm Intelligence’. Existing ant- clustering algorithm uses two user defined parameters to calculate the picking-up probability and dropping probability those are used to form the cluster. But, use of user defined parameters may lead to form an inaccurate cluster. It is difficult to anticipate about the value of the user defined parameters in advance to form the cluster because of the diversified characteristics of the dataset. In this paper, we have analyzed the existing ant-clustering algorithm and then numerical analysis method of linear equation is proposed based on the characteristics of the dataset that does not need any user defined parameters to form the clusters. Results of numerical experiments on synthetic datasets demonstrate the effectiveness of the proposed method.
关键词：Ant-Clustering Algorithm; Swarm Intelligence; Numerical Method; Linear Equations