a genetic clustering algorithm using a message-based similarity measure
文献类型：会议论文
| 作者 | Chang Dongxia ; Zhao Yao ; Zheng Changwen ; Zhang Xianda |
| 出版日期 | 2011 |
| 关键词 | Chromosomes Gallium alloys Genetic algorithms Mathematical operators Message passing Real variables |
| 页码 | - |
| 英文摘要 | 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. |
| 收录类别 | EI |
| 会议录 | Expert Systems with Applications
 |
| 语种 | 英语 |
| ISSN号 | 9574174 |
| WOS记录号 | WOS:000298027300063 |
| 源URL | [http://124.16.136.157/handle/311060/14387]  |
| 专题 | 软件研究所_综合信息系统技术国家级重点实验室 _会议论文 |
| 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]. 见:. |
入库方式： OAI收割
来源：软件研究所
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