Fuzzy C-means algorithm based on simulated annealing Particle Swarm Optimization

doi:10.3778/j.issn.1002-8331.2008.30.052

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (30): 170-172.DOI: 10.3778/j.issn.1002-8331.2008.30.052

• 数据库、信号与信息处理 • Previous Articles Next Articles

Fuzzy C-means algorithm based on simulated annealing Particle Swarm Optimization

LI Li-li¹,LIU Xi-yu²,ZHUANG Bo³

1.School of Information Science and Engineering，Shandong Normal University，Jinan 250014，China
2.School of Management，Shandong Normal University，Jinan 250014，China
3.Department of Computer Science and Technology，Binzhou University，Binzhou，Shandong 256603，China

Received:2007-11-23 Revised:2008-01-28 Online:2008-10-21 Published:2008-10-21
Contact: LI Li-li

基于模拟退火粒子群算法的FCM聚类方法

李丽丽¹,刘希玉²,庄波³

1.山东师范大学信息科学与工程学院，济南 250014
2.山东师范大学管理与经济学院，济南 250014
3.滨州学院计算机科学技术系，山东滨州 256603

通讯作者: 李丽丽

Abstract

Abstract: In order to overcome the defects of fuzzy C-means algorithm such as the local optima and sensitivity to initialization，a new fuzzy algorithm based on SA-PSO is put forward in this paper．The new algorithm makes use of the capacity of global search in PSO algorithm and the ability of jumping out of the local optima in SA，and solves the shortcomings of FCM.The experiment shows that the algorithm avoids the local optima and increases the convergence speed.

Key words: cluster analysis, simulated annealing, Particle Swarm Optimization（PSO）, fuzzy C-mean algorithm, global optimization

摘要： 针对模糊C-均值（FCM）聚类算法易陷入局部极小值和对初始值敏感的缺点，提出了一种基于模拟退火粒子群优化的模糊聚类算法。该算法利用粒子群强大的全局寻优能力和模拟退火算法跳出局部极值的能力，克服了模糊C-均值聚类算法的不足。实验表明，该算法有很好的全局收敛性，能够较快地收敛到最优解。

关键词: 聚类分析, 模拟退火算法, 粒子群优化算法, 模糊C-均值算法, 全局优化

LI Li-li¹,LIU Xi-yu²,ZHUANG Bo³. Fuzzy C-means algorithm based on simulated annealing Particle Swarm Optimization[J]. Computer Engineering and Applications, 2008, 44(30): 170-172.

李丽丽¹,刘希玉²,庄波³. 基于模拟退火粒子群算法的FCM聚类方法[J]. 计算机工程与应用, 2008, 44(30): 170-172.

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Fuzzy C-means algorithm based on simulated annealing Particle Swarm Optimization

基于模拟退火粒子群算法的FCM聚类方法

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