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《Automation of Electric Power Systems》 2001-15
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A NEW DATA MINING APPROACH FOR FAULT DIAGNOSIS OF HIGH VOLTAGE TRANSMISSION LINE BASED ON ROUGH SET THEORY

Liao Zhiwei,Sun Yaming Tianjin University,Tianjin 30 0 0 72 ,China  
In most practical application of fault diagnosis system ,misjudgem ent may be caused by real- time information distorted in the process of generation and transfer.This paper presents rough set RS based data mining m ethod to deal with distorted inform ation and to im plem ent the fault diagnosis of HV transm ission line system HVTL S .In this approach,the qualitative analysis ability of RS is used to analyze knowledge region data set and the reductions of RS are solved by a genetic algorithm GA .At same time,this paper proposes the criterion to build testing sam ples,in order to get the assurance of fault tolerance perform ance of tested diagnosis system and have practical application potential of studied system .The higher fault tolerance perform ance of the proposed approach is confirmed through the com parison with that of NN- model based fault diagnosis system.
【Fund】: 国家自然科学基金资助项目 (5 98770 16 )
【CateGory Index】: TM723
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