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基于区域等分的改进K-Means算法研究

发表时间:2013-09-30  浏览量:1191  下载量:596
全部作者: 肖建铃,陈国良
作者单位: 中国矿业大学环境与测绘学院,江苏省资源环境信息工程重点实验室
摘 要: 从提高聚类质量的角度出发,借鉴区域划分思想,结合传统的K-Means算法,提出了基于区域等分的K-Means改进算法。改进的K-Means算法在保证聚类质量的前提下,聚类效率显著提高,并且聚类结果非常稳定。研究表明:改进算法的结果提高了传统K-Means算法的性能,改进结果令人满意。
关 键 词: 摄影测量与遥感技术;K-Means;划分;算法
Title: Study of improved K-Means algorithm based on equal region division
Author: XIAO Jianling, CHEN Guoliang
Organization: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment and Spatial Informatics, China University of Mining and Technology
Abstract: In this paper, according to the prospective of increasing clustering quality, referring the thought of region division, and combining the traditional K-Means algorithms, the improved K-Means algorithms based on equal region division was put forward. The improved K-Means not only guaranteed clustering quality, but increased clustering efficiency significantly as well. The clustering results obtained were very stable. The study showed that the improved algorithm could enhance the performance of traditional K-Means algorithms, and the improved results were satisfactory.
Key words: photogrammetry and remote sensing technology; K-Means; division; algorithm
发表期数: 2013年9月第18期
引用格式: 肖建铃,陈国良. 基于区域等分的改进K-Means算法研究[J]. 中国科技论文在线精品论文,2013,6(18):1784-1788.
 
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