A Power Grid Fault Diagnosis Method based on Ensemble Decision Tree

被引：0
|
作者：
Wang, Ding [1 ]
Li, Guang [1 ]
Tang, Weining [1 ]
Tian, Chunguang [1 ]
Zhou, Hongwei [1 ]
机构：
[1] State Grid Jilin Elect Power Co Ltd, Elect Power Res Inst, Changchun 130021, Jilin, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE) | 2017年 / 190卷
关键词：
SYSTEMS;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The reason for the failure of the grid is complicated. On the one hand, because the majority of the information comes from the grid signal whose description dimension is higher; on the other hand, it is a low probability that large number or types of fault problems occur in one area. To solve this problem, this paper proposed a power grid fault diagnosis method based on ensemble decision tree (PGFD-EDT). This algorithm uses attribute selection mechanism to divide a large number of power signal attributes for multiple sets of attribute subsets, each subset is trained individually for a decision tree, and multiple decision tree models vote together to determine the grid failure. Experiments show that the PGFD-EDT algorithm has higher stability and accuracy.
引用
收藏
页码：367 / 372
页数：6
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