A novel fuzzy clustering based on particle swarm optimization

被引：0
|
作者：
Li, Lili [1 ]
Liu, Xiyu [2 ]
Xu, Mingming [3 ]
机构：
[1] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan, Shandong, Peoples R China
[2] Shandong Normal Univ, Sch Management, Jinan 250014, Shandong, Peoples R China
[3] Ping An China Co Ltd, Jinan 250001, Peoples R China
来源：
PROCEEDINGS OF THE 2007 1ST INTERNATIONAL SYMPOSIUM ON INFORMATION TECHNOLOGIES AND APPLICATIONS IN EDUCATION (ISITAE 2007) | 2007年
关键词：
cluster analysis; particle swarm optimization; fuzzy C-means algorithm; global optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to overcome the shortcomings of Fuzzy C-means Algorithm such as the local optima and sensitivity to initialization, a new PSO-based fuzzy algorithm is discussed in this paper. The new algorithm uses the capacity of global search in PSO algorithm, and solves the problems of FCM. The experiment shows that the algorithm avoids the local optima and increases the convergence speed.
引用
收藏
页码：88 / +
页数：2
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