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《Electronics Optics & Control》 2009-03
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Application of Rough Set and Support Vector Machine in Complex Circuit System Diagnosis

MA Chenguang,HU Changhua,LUO Gongchun,ZHENG Jianfei (The Second Artillery Engineering Institute,Xi'an 710025,China)  
In complex circuit system,it is lack of fault samples and the feature information is miscellaneous and redundant.To solve the problem,a new fault diagnosis method was presented based on Rough Set(RS) and Support Vector Machine(SVM).The RS was applied to reduce the redundant attributes and the conflicting samples.Then the simplest fault attributes were extracted as the training samples for SVM,which was used as the classifier to isolate the faults rapidly.The simulated experiments demonstrated that the method is valid and feasible under the condition of small samples.
【Fund】: 国家自然科学基金重点课题(60736026);; 国家教育部新世纪优秀人才支持计划项目
【CateGory Index】: TP18;TN707
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