Multi-BP expert system for fault diagnosis of power system

被引：72

作者：

Ma, Deyin ^{[1
]}

Liang, Yanchun ^{[1
]}

Zhao, Xiaoshe ^{[1
]}

Guan, Renchu ^{[1
]}

Shi, Xiaohu ^{[1
]}

机构：

[1] Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Coll Comp Sci & Technol, Changchun 130023, Peoples R China

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2013年 / 26卷 / 03期

基金：

中国博士后科学基金; 中国国家自然科学基金;

关键词：

Power system; Expert system; Multi-BP networks; CLASSIFICATION;

D O I：

10.1016/j.engappai.2012.03.017

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Fault diagnosis and assessment is a crucial and difficult problem for power system. Back propagation neural network expert system (BPES) is an often used method in fault diagnosis. However, with the layer numbers increasing, BPES becomes time consuming and even hard to converge. To solve this problem, we divide the whole networks into many sub-BP groups within a short depth and then propose a novel Multi-BP expert system (MBPES) based method for power system fault diagnosis. We use two real power system data sets to test the effectiveness of MBPES. Experimental results show that MBPES obtains higher accuracy than two commonly used methods. (c) 2012 Elsevier Ltd. All rights reserved.

引用

页码：937 / 944

页数：8

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