{"title":"基于BP神经网络的故障诊断专家系统","authors":"Rong Hua, Chen Qiu","doi":"10.1109/IAEAC.2015.7428684","DOIUrl":null,"url":null,"abstract":"This paper summarizes the features and principles of artificial neural network, and problems existing in the traditional expert system. Then it introduces the structural components and advantages of fault diagnosis system which combined with artificial neural network and expert system. Finally it elaborates the basic principle and implementation process of fault diagnosis expert system based on BP neural network.","PeriodicalId":398100,"journal":{"name":"2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"The fault diagnosis expert system based on BP neural network\",\"authors\":\"Rong Hua, Chen Qiu\",\"doi\":\"10.1109/IAEAC.2015.7428684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper summarizes the features and principles of artificial neural network, and problems existing in the traditional expert system. Then it introduces the structural components and advantages of fault diagnosis system which combined with artificial neural network and expert system. Finally it elaborates the basic principle and implementation process of fault diagnosis expert system based on BP neural network.\",\"PeriodicalId\":398100,\"journal\":{\"name\":\"2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAEAC.2015.7428684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC.2015.7428684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The fault diagnosis expert system based on BP neural network
This paper summarizes the features and principles of artificial neural network, and problems existing in the traditional expert system. Then it introduces the structural components and advantages of fault diagnosis system which combined with artificial neural network and expert system. Finally it elaborates the basic principle and implementation process of fault diagnosis expert system based on BP neural network.