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CHEN Xing-yu
Xi’an Technological University

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Distribution Network Fault Diagnosis Method Based on Granular Computing-BP CHEN Zhong-xiao; CUI Ke; CHEN Xing-yu; LI Yan-fang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: March 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

To deal with the complexity and uncertainty of distribution network fault information, a method of fault diagnosis based on granular computing and BP is proposed. This method uses attribute reduction advantages of granular computing theory and self-learning and knowledge acquisition ability of BP neural network. It put granular computing theory as the front-end processor of the BP neural network, namely simplify primitive information making use of granular computing reduction, and according to the concepts of relative granularity and significance of attributes based on binary granular computing are proposed to select input of BP, thereby reducing solving scale, and then construct neural network based on the minimum attribute sets, using BP neural network to model and parameter identify, reduce the BP study training time, improve the accuracy of the fault diagnosis. The distribution network example verifies the rationality and effectiveness of the proposed method.DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2184
Co-Authors CHEN Zhong-xiao CUI Ke LI Yan-fang