桂林电子科技大学学报2017，Vol.37Issue(5)：406-410,5.
一种面向电力用户细分的鲁棒k-means算法
A robust k-means algorithm for power user segmentation
摘要
Abstract
In order to solve the problem that the traditional k-means algorithm is sensitive to the selection of the initial cluste-ring center and the number of clusters is specified in advance,a robust k-means (Rk-means)algorithm is proposed.The im-proved MaxMin initialization method is used to solve the initial cluster center selection sensitive problem.Through the mass of the user information critical clustering information identification,the automatic clustering is done.The experimental re-sults show that the algorithm is effective and robust,and the algorithm is applied to the power customer segmentation, which can help the power supply enterprises to make the correct power marketing strategy.关键词
k-means/聚类中心选择/自动分裂和合并簇/电力客户细分Key words
k-means/cluster centers selection/automatically splitting and merging clusters/electricity customer segmenta-tion分类
信息技术与安全科学引用本文复制引用
李倩,王恩伟,雷景生,宋硕..一种面向电力用户细分的鲁棒k-means算法[J].桂林电子科技大学学报,2017,37(5):406-410,5.基金项目
国家自然科学基金(61602295) （61602295）
