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

页码：1442 / 1445

页数：4

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