{"title":"BP神经网络在机械故障分类中的应用","authors":"Fang Zhou, Jianheng Ji, De-zhen Feng","doi":"10.1109/IWISA.2009.5073165","DOIUrl":null,"url":null,"abstract":"Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"92 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Application of BP Neural Network on Mechanical Failure Classification\",\"authors\":\"Fang Zhou, Jianheng Ji, De-zhen Feng\",\"doi\":\"10.1109/IWISA.2009.5073165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation\",\"PeriodicalId\":6327,\"journal\":{\"name\":\"2009 International Workshop on Intelligent Systems and Applications\",\"volume\":\"92 1\",\"pages\":\"1-3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2009.5073165\",\"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 International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2009.5073165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Application of BP Neural Network on Mechanical Failure Classification
Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation