Using glowworm swarm optimization algorithm for clustering analysis

被引：15

作者：

Huang Z. ^{[1
]}

Zhou Y. ^{[1
]}

机构：

[1] College of Mathematics and Computer Science, Guangxi University for Nationalities

来源：

Journal of Convergence Information Technology | 2011年 / 6卷 / 02期

关键词：

Clustering analysis; Glowworm swarm optimization; Self-organization clustering; Swarm-based clustering;

D O I：

10.4156/jcit.vol6.issue2.9

中图分类号：

学科分类号：

摘要：

In this paper, two new cluster analysis methods based on glowworm swarm optimization (GSO) algorithm are proposed. The first algorithm showed how GSO can be used to self-organization cluster analysis. The second algorithm is hybrid the GSO clustering analysis with the K-means algorithm to accelerate classification. Two clustering algorithms are tested on three data sets; experimental results show that the two kind of clustering algorithm has higher clustering results.

引用

页码：78 / 85

页数：7

共 13 条

[1]

Handl J., Meyer B., Ant-based and swarm-based clustering, Swarm Intell, 1, pp. 95-113, (2007)

[2]

Krishnand K.N., Ghose D., Glowworm swarm optimisation: A new method for optimising multimodal functions, Int. J. Computational Intellingence Studies, 1, 1, pp. 93-119, (2009)

[3]

Krishnand K.N., Ghose D., Glowworm swarm optimisation for simultaneous Capture of mutiple local optima of multimodal functions, Swarm Intell, 3, pp. 87-124, (2009)

[4]

Rui X., Survey of clustering algorithms, IEEE Transactions On Neural Networks, 16, 3, pp. 645-678, (2005)

[5]

Jain A.K., Murty M.N., Flynn P.J., Data Clustering: A Review. ACM Computing Surveys, 31, 3, pp. 264-323, (1999)

[6]

vander Merwe D.W., Engelhrecht A.P., Data Clustering Using Particle Swarm Optimization, 1, pp. 215-220, (2003)

[7]

Niknam T., Firouzi B.B., Nayeripour M., An efficient hybrid evolutionary algorithm for cluster analysis, World Applied Sciences Journal, 4, 2, pp. 300-307, (2008)

[8]

Bai L., Yongquan Z., Mixed clustering algorithm based on artificial fish swarm, Computer Engineering and Applications, 44, 18, pp. 136-138, (2008)

[9]

Jin-Xin D., Qi M.-Y., New clustering algorithm based on particle swarm optimization and simulated annealing, Computer Engineering and Applications, 45, 35, pp. 139-141, (2009)

[10]

Sun J.G., Liu J., Zhao L.Y., Clustering algorithms research, Journal of Software, 19, 1, pp. 48-61, (2008)

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