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文章摘要
基于改进GA优化T-S模糊神经网络的小电流接地故障选线方法
Fault line selection method for small current grounding based on improved GA to optimize T-S fuzzy neural network
Received:May 22, 2015  Revised:August 17, 2015
DOI:
中文关键词: 小电流接地系统  单相接地  选线  改进GA  T-S模糊神经网络
英文关键词: small  current grounding  system, single-phase  grounding, line  selection, improved  GA, T-S  fuzzy neural  network
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(1408085MKL13)
Author NameAffiliationE-mail
Wang Lei School of Electrical Engineering and Automation,Hefei University of Technology 6273419@qq.com 
Cao Xianfeng* School of Electrical Engineering and Automation,Hefei University of Technology 137687360@qq.com 
Luo Wei School of Electrical Engineering and Automation,Hefei University of Technology  
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中文摘要:
      在小电流接地系统中,发生最多的是单相接地故障,针对如何快速准确地查找故障线路一直都是重点研究课题,且没有得到有效的解决。本文提出一种基于改进遗传算法(GA)优化T-S模糊神经网络的配电网故障选线方法:通过改进GA的适应度函数,先对网络初始参数、权值进行一次优化后,使用梯度下降法进行二次优化的选线算法。讨论了T-S模糊神经网络,传统GA优化的T-S模糊神经网络及不同网络结构对网络性能的影响。研究结果表明改进GA优化T-S模糊神经网络的选线效果明显优于T-S模糊神经网络和传统GA优化T-S模糊神经网络,能够快速、准确、可靠的选取故障线路。
英文摘要:
      In the small current grounding system, the most is single-phase grounding fault. how to quickly and accurately find the fault line has been a key research topic, and this didn"t get effective solution. This paper presents a fault line selection method of power distribution network based on improved genetic algorithm (GA) to optimize T-S fuzzy neural network. By improving the fitness function of GA, initial parameters and weights are optimized firstly, using the gradient descent method to optimize the second time. the influence of T-S fuzzy neural network, the traditional GA optimization of T-S fuzzy neural network and different network structures to network performance are discussed. The results of the study illustrate the improved 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, can accurately, effectively, reliablely find fault line.
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