Adaptive K-valued K-means clustering algorithm

被引：1
|
作者：
Wang Shenghui [1 ]
Li Hanbing [1 ]
机构：
[1] Changchun Univ Technol, Sch Elect & Elect Engn, Changchun, Peoples R China
来源：
2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020) | 2020年
关键词：
K value; PSO algorithm; K - means algorithm;
D O I：
10.1109/ICMCCE51767.2020.00316
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Based on particle swarm optimization (PSO), the algorithm for selecting appropriate K values is improved by combining k-mean algorithm. When the algorithm converges, the expansion and reduction of K value can be determined by comparing the relationship between different K value selection and global optimal fitness. Experiments show that the improved algorithm can assist K value selection effectively and obtain a better clustering effect.
引用
收藏
页码：1442 / 1445
页数：4
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