Clustering Algorithm based on Immunological Partheno Genetic and Fuzzy C-Means

摘要：

Clustering algorithm is an important way of the data mining.This paper analyzes the lack of FCM algorithm and genetic clustering algorithm.Propose a hybrid clustering algorithm based on immune single genetic and fuzzy C-means.This algorithm not only overcomes the local optimal problem of FCM because of the inappropriate choice of the initial value, but also overcomes the contradictions between the search speed and clustering accuracy of the general genetic clustering algorithm.Experiments show that the algorithm is effective.

关键词： Clustering analysis genetic algorithm FCM Immune mechanism

作者: Hongfen Jiang Mingfang Zhu Yijun Liu Guangping Zhu Dan Chen Junfeng Gu

作者单位: College of Computer Engineering,Jiangsu Teachers University of Technology Changzhou,China College of Petroleum Engineering,Changzhou University Changzhou,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 226-229

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）