文章基本信息

标题：Fault Analysis for Power Network Equipment Based On Association Rule Clustering Algorithm
本地全文：下载
作者：Zhang Hu ; Li Feng ; Wang Hongbin 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：8
页码：115-124
出版社：SERSC
摘要：In order to improve the fault positioning accuracy of distributed generation power distribution network, it puts forward fault positioning method of distribution network equipment based on blended data association rule data mining method. Based on fuzzy rough set theory, it studies classification rule mining method on hybrid data, through the introduction of the rule to obtain the a generalized threshold of the algorithm, and control the scale and complexity of the obtained rule set, so as to improve the classification efficiency of rough set method of knowledge discovery on the failure data and get the fault positioning feature of distribution network, finally adopts the support vector machine (SVM) to make fault classification, and tests the performance of the algorithm with simulation experiment. The simulation results show that, this paper can be quickly and accurately to locate fault power section, and the fault positioning accuracy is higher than other fault positioning methods of distribution network.
关键词：Rough set; fault positioning; Association rule; Power grid equipment; ;Modal data