ISCAS OpenIR
A novel genetic clustering algorithm with variable-length chromosome representation
Zhang, Ming-An (1); Deng, Yong (1); Chang, Dong-Xia (2)
2014
Conference Name16th Genetic and Evolutionary Computation Conference, GECCO 2014
Pages1483-1484
Conference DateJuly 12, 2014 - July 16, 2014
Conference PlaceVancouver, BC, Canada
Indexed TypeEI
Publish PlaceAssociation for Computing Machinery
ISBN9781450328814
Department(1) Institute of Software, Chinese Academy of Sciences, 4# South Fourth Street, Zhongguancun, Beijing 100190, China; (2) Institute of Information Science, Beijing Jiaotong University, No.3 Shang Yuan Cun, Hai Dian District Beijing 100040, China
English AbstractThe paper proposed a new genetic clustering algorithm with variable-length chromosome representation(GCVCR), which can automatically evolve and find the optimal number of clusters as well as proper cluster centers of the data set. A new clustering criterion based on message passing between data points and the candidate centers described by the chromosome are presented to make the clustering problem more effective. The simulation results show the effectiveness of the proposed algorithm.; The paper proposed a new genetic clustering algorithm with variable-length chromosome representation(GCVCR), which can automatically evolve and find the optimal number of clusters as well as proper cluster centers of the data set. A new clustering criterion based on message passing between data points and the candidate centers described by the chromosome are presented to make the clustering problem more effective. The simulation results show the effectiveness of the proposed algorithm.
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16578
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Zhang, Ming-An ,Deng, Yong ,Chang, Dong-Xia . A novel genetic clustering algorithm with variable-length chromosome representation[C]. Association for Computing Machinery,2014:1483-1484.
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