电测与仪表2016，Vol.53Issue(17)：6-11,6.
基于 GA 优化 T－S 模糊神经网络的小电流接地故障选线新方法
New method of fault line selection for small current grounding based on GA tooptimize T-S fuzzy neural network
摘要
Abstract
In the small current grounding system , the single-phase grounding fault happens frequently .How to quick-ly and accurately find the fault line has been a key research topic , and this doesn ’ t get effective solution .This paper presents a new method offault line selectionforpower distribution network based on genetic algorithm ( GA) to optimize T-S fuzzy neural network .By adjustingthe fitness function of traditionalGA , initial parameters andweights are opti-mized firstly , and the gradient descent method is used to optimize the second time .The influence of T-S fuzzy neural network , the traditional GA optimization of T-S fuzzy neural network and differentnetwork structures to network perfor-manceare discussed .The results of the studyillustrate the new GA to optimize T-S fuzzy neural network is better than T-S fuzzy neural network and traditional GA to optimize T -S fuzzy neural network in the term of line selection effect , which can accurately , effectively , andreliably select the fault line .关键词
小电流接地系统/单相接地/选线/GA/T-S模糊神经网络Key words
smallcurrent grounding system/single-phase grounding/line selection/GA/T-S fuzzy neural network分类
信息技术与安全科学引用本文复制引用
王磊,曹现峰,骆玮..基于 GA 优化 T－S 模糊神经网络的小电流接地故障选线新方法[J].电测与仪表,2016,53(17):6-11,6.基金项目
国家自然科学基金资助项目（51177036）；安徽省自然科学基金资助项目 （）
