计算机科学技术 |
|
|
|
|
基于多染色体演化的自适应类别数聚类方法 |
倪广翼, 章孝灿, 苏程, 俞伟斌 |
浙江大学 地球科学系, 浙江 杭州 310027 |
|
Count adaptive clustering algorithm based on multiple-chromosome evolution |
NI Guang-yi, ZHANG Xiao-can, SU Cheng, YU Wei-bin |
Department of Geoscience, Zhejiang University, Hangzhou 310027, China |
[1] FALKENAUER E. Genetic Algorithms and Grouping Problems[M]. New York, USA: Wiley, 1998.
[2] HRUSCHKA E R, CAMPELLO R J G B, FREITAS A A, et al. A survey of evolutionary algorithms for clustering[J]. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 2009, 39(2): 133-155.
[3] FRNTI P, KIVIJRVI J, KAUKORANTA T, et al. Genetic algorithms for large-scale clustering problems[J]. The Computer Journal, 1997, 40(9): 547-554.
[4] LU Y, LU S, FOTOUHI F, et al. FGKA: A fast genetic k-means clustering algorithm[C] ∥ Proceedings of the 2004 ACM Symposium on Applied Computing. New York, USA: ACM, 2004: 622-623.
[5] KRISHNA K, MURTY M N. Genetic K-means algorithm[J]. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 1999, 29(3): 433-439.
[6] SEO H S, OH S J, LEE C W. Evolutionary genetic algorithm for efficient clustering of wireless sensor networks[C]∥ Consumer Communications and Networking Conference, 2009. CCNC 2009. 6th IEEE. Las Vegas, USA: IEEE, 2009: 15.
[7] HRUSCHKA E R, CAMPELLO R J G B, DE CASTRO L N. Evolving clusters in gene-expression data[J]. Information Sciences, 2006, 176(13): 1898-1927.
[8] ALVES V S, CAMPELLO R J G B, HRUSCHKA E R. Towards a fast evolutionary algorithm for clustering[C]∥ Evolutionary Computation, 2006. CEC 2006. IEEE Congress on. Vancouver, Canada: IEEE, 2006: 1776-1783.
[9] HRUSCHKA E R, EBECKEN N F F. A genetic algorithm for cluster analysis[J]. Intelligent Data Analysis, 2003, 7(1): 15-25.
[10] HANDL J, KNOWLES J. An evolutionary approach to multiobjective clustering[J]. Evolutionary Computation, IEEE Transactions on, 2007,11(1): 56-76.
[11] 赖玉霞, 刘建平, 杨国兴. 基于遗传算法的 K 均值聚类分析[J]. 计算机工程, 2008, 34(20): 200-202.
LAI Yu-xia, LIU Jian-ping, YANG Guo-xing. K-Means clustering analysis based on genetic algorithm[J]. Computer Engineering, 2008, 34(20): 200-202.
[12] MAULIK U, BANDYOPADHYAY S. Fuzzy partitioning using a real-coded variable-length genetic algorithm for pixel classification[J]. Geoscience and Remote Sensing, IEEE Transactions on, 2003, 41(5): 1075-1081.
[13] KWEDLO W. A clustering method combining differential evolution with the K-means algorithm[J]. Pattern Recognition Letters, 2011, 32(12): 1613-1621.
[14] 何宏, 谭永红. 一种基于动态遗传算法的聚类新方法[J]. 电子学报, 2012, 40(2): 254-259.
HE Hong, TAN Yong-hong. A novel clustering method based on dynamic genetic algorithm[J]. Acta Electronica Sinica, 2012, 40(2): 254-259.
[15] BANDYOPADHYAY S, MAULIK U. An evolutionary technique based on K-means algorithm for optimal clustering in RN[J]. Information Sciences, 2002, 146(1): 221-237.
[16] 钟将,吴中福,吴开贵,等.基于人工免疫网络的动态聚类算法[J].电子学报,2004, 32(8): 1268-1272.
ZHONG Jiang, WU Zhong-fu, WU Kai-gui, et al. A novel dynamic clustering algorithm based on artificial immune network[J]. Acta Electronica Sinica, 2004, 32(8): 1268-1272.
[17] BANDYOPADHYAY S, MAULIK U. Genetic clustering for automatic evolution of clusters and application to image classification[J]. Pattern Recognition, 2002, 35(6): 1197-1208.
[18] HORTA D, NALDI M, CAMPELLO R, et al. Evolutionary fuzzy clustering: an overview and efficiency issues[M]∥ Foundations of Computational Intelligence Volume 4. Berlin Heidelberg: Springer,2009: 167-195.
[19] PLACKETT R L. Karl Pearson and the chi-squared test[EB/OL]. \[2012-12-19\]. htpp:∥as. wiley. com/wiley CDA/Wiley Title/productCd-INSR. html. 1983: 59-72.
[20] STORN R, PRICE K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11(4): 341-359.
[21] DEMPSTER A P, LAIRD N M, RUBIN D B. Maximum likelihood from incomplete data via the EM algorithm[J]. Journal of the Royal Statstical Society. Series B (Methodological), 1977,39(1): 138.
[22] FRANK A, ASUNCION A. UCI machine learning repository [DB/OL]. [2013-02-23].http: ∥archive.ics.uci.edu/ml/datasets/Iris.
[23] NALDI M C, CAMPELLO R, HRUSCHKA E R, et al. Efficiency issues of evolutionary k-means[J]. Applied Soft Computing, 2011, 11(2): 1938-1952. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|