Data clustering using particle swarm optimization

被引：439

作者：

van der Merwe, D ^{[1
]}

Engelbrecht, AP ^{[1
]}

机构：

[1] Univ Pretoria, Dept Comp Sci, ZA-0002 Pretoria, South Africa

来源：

CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS | 2003年

关键词：

D O I：

10.1109/CEC.2003.1299577

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper proposes two new approaches to using PSO to cluster data. It is shown how PSO can be used to find the centroids of a user specified number of clusters. The algorithm is then extended to use K-means clustering to seed the initial swarm. This second algorithm basically uses PSO to refine the clusters formed by K-means. The new PSO algorithms are evaluated on six data sets, and compared to the performance of K-means clustering. Results show that both PSO clustering techniques have much potential.

引用

页码：215 / 220

页数：6

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