a genetic clustering algorithm using a message-based similarity measure
Chang Dongxia; Zhao Yao; Zheng Changwen; Zhang Xianda
2011
会议录名称Expert Systems with Applications
页码-
收录类别ei
ISSN9574174
部门归属(1) Institute of Information Science, Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China; (2) National Key Lab of Integrated Information System Technology, Institute of Software, Chinese Academy of Sciences, Beijing 100080, China; (3) Tsinghua Department of Automation, Tsinghua University, Beijing 100084, China
摘要In this paper, a genetic clustering algorithm is described that uses a new similarity measure based message passing between data points and the candidate centers described by the chromosome. In the new algorithm, a variable-length real-value chromosome representation and a set of problem-specific evolutionary operators are used. Therefore, the proposed GA with message-based similarity (GAMS) clustering algorithm is able to automatically evolve and find the optimal number of clusters as well as proper clusters of the data set. Effectiveness of GAMS clustering algorithm is demonstrated for both artificial and real-life data set. Experiment results demonstrated that the GAMS clustering algorithm has high performance, effectiveness and flexibility. © 2011 Elsevier Ltd. All rights reserved.
关键词Chromosomes Gallium Alloys Genetic Algorithms Mathematical Operators Message Passing Real Variables
语种英语
WOS记录号WOS:000298027300063
引用统计
被引频次:22[WOS]   [WOS记录]     [WOS相关记录]
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/14387
专题天基综合信息系统全国重点实验室
推荐引用方式
GB/T 7714
Chang Dongxia,Zhao Yao,Zheng Changwen,et al. a genetic clustering algorithm using a message-based similarity measure[C],2011:-.
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