{"title":"电子电路故障诊断的神经网络新方法","authors":"WenJie Tian, Yu Geng","doi":"10.1109/ETCS.2009.318","DOIUrl":null,"url":null,"abstract":"To overcome the deficiencies of single neural network such as low diagnosis precision, long training time and bad generalized ability, an integrated neural network classifier is proposed for electronic circuit fault diagnosis in the paper. The investigation shows that the proposed method has higher classification precision and reliability, and is an ideal pattern classifier. Both simulation and experiment indicate that the proposed method is quite effective and ubiquitous.","PeriodicalId":422513,"journal":{"name":"2009 First International Workshop on Education Technology and Computer Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Neural Network Approach to Electronic Circuit Fault Diagnosis\",\"authors\":\"WenJie Tian, Yu Geng\",\"doi\":\"10.1109/ETCS.2009.318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To overcome the deficiencies of single neural network such as low diagnosis precision, long training time and bad generalized ability, an integrated neural network classifier is proposed for electronic circuit fault diagnosis in the paper. The investigation shows that the proposed method has higher classification precision and reliability, and is an ideal pattern classifier. Both simulation and experiment indicate that the proposed method is quite effective and ubiquitous.\",\"PeriodicalId\":422513,\"journal\":{\"name\":\"2009 First International Workshop on Education Technology and Computer Science\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 First International Workshop on Education Technology and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETCS.2009.318\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 First International Workshop on Education Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCS.2009.318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Neural Network Approach to Electronic Circuit Fault Diagnosis
To overcome the deficiencies of single neural network such as low diagnosis precision, long training time and bad generalized ability, an integrated neural network classifier is proposed for electronic circuit fault diagnosis in the paper. The investigation shows that the proposed method has higher classification precision and reliability, and is an ideal pattern classifier. Both simulation and experiment indicate that the proposed method is quite effective and ubiquitous.