A Geometry-Based Accelerated Fusion Clustering Algorithm and its Application in Marine Engineering

被引：1

作者：

Wang Tianzhen ^{[1
]}

Liu Yang ^{[1
]}

Tang Tianhao ^{[1
]}

机构：

[1] Shanghai Maritime Univ, Shanghai, Peoples R China

来源：

PROGRESS IN MEASUREMENT AND TESTING, PTS 1 AND 2 | 2010年 / 108-111卷

关键词：

Data mining; clustering analysis; k-means plus; computational complexity;

D O I：

10.4028/www.scientific.net/AMR.108-111.106

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In order to solve the problem in k-means algorithm that inappropriate selection of initial clustering centers often causes clustering in local optimum and the time complexity is too high when handling large amounts of data, a fusion clustering algorithm based on geometry is proposed in this paper. The result of experiments shows this algorithm is better than the traditional k-means and the k-means++ algorithms, with higher quality and faster speed. And at last in this paper, we apply it in marine engineering.

引用

页码：106 / 111

页数：6