Hybridization Clustering Algorithm of Particle Swarm  Optimization Based on Density

doi:10.3969/j.issn.1000-3428.2007.08.059

Computer Engineering ›› 2007, Vol. 33 ›› Issue (08): 170-172. doi: 10.3969/j.issn.1000-3428.2007.08.059

• Artificial Intelligence and Recognition Technology • Previous Articles Next Articles

Hybridization Clustering Algorithm of Particle Swarm Optimization Based on Density

SHAN Shimin1, DENG Guishi1, HE Yinghao2

(1. Institute of Systems Engineering, Dalian University of Technology, Dalian 116023; 2. City Institute, Dalian University of Technology, Dalian 116600)

Received:1900-01-01 Revised:1900-01-01 Online:2007-04-20 Published:2007-04-20

基于密度的微粒群优化混合聚类算法

单世民1，邓贵仕1，何英昊2

(1. 大连理工大学系统工程研究所，大连 116023；2. 大连理工大学城市学院，大连 116600)

Abstract

Abstract: A hybridization of the PSO with density-based clustering algorithm is presented in the paper. The algorithm is suitable to process the incremental data compared to the DENCLUE. Besides, the resource used in the algorithm is limited. Several experiments are performed to test the algorithm. The results indicate the efficiency of the algorithm.

Key words: Clustering, Particle swarm optimization (PSO), Density-based clustering

摘要： 在分析了现有的基于密度的聚类算法的基础上，结合微粒群算法，提出了一种基于密度的微粒群混合聚类算法。相对于DENCLUE聚类算法，该算法能够对使用的资源进行有效的控制，有利于实现对数据库数据的增量处理。实验证明了算法的有效性。

关键词: 聚类, 微粒群优化, 密度聚类

CLC Number:

TP301.6

SHAN Shimin; DENG Guishi; HE Yinghao. Hybridization Clustering Algorithm of Particle Swarm Optimization Based on Density[J]. Computer Engineering, 2007, 33(08): 170-172.

单世民;邓贵仕;何英昊. 基于密度的微粒群优化混合聚类算法[J]. 计算机工程, 2007, 33(08): 170-172.

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