{"title":"基于改进Bp神经网络的软件可靠性模型研究","authors":"Li Mei","doi":"10.1109/ICSGEA.2018.00061","DOIUrl":null,"url":null,"abstract":"Neural network has good fault-tolerant ability, classification ability, parallel processing ability and so on, so the research of software reliability model based on neural network is paid more and more attention. Bp neural network has strong nonlinear mapping ability and flexible network structure, so BP neural network is currently used in various fields. In this paper, a software reliability model optimized by hidden layer BP neural network is proposed and the training process of BP algorithm on this model is described.","PeriodicalId":445324,"journal":{"name":"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on Software Reliability Model Based on Improved Bp Neural Network\",\"authors\":\"Li Mei\",\"doi\":\"10.1109/ICSGEA.2018.00061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neural network has good fault-tolerant ability, classification ability, parallel processing ability and so on, so the research of software reliability model based on neural network is paid more and more attention. Bp neural network has strong nonlinear mapping ability and flexible network structure, so BP neural network is currently used in various fields. In this paper, a software reliability model optimized by hidden layer BP neural network is proposed and the training process of BP algorithm on this model is described.\",\"PeriodicalId\":445324,\"journal\":{\"name\":\"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSGEA.2018.00061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSGEA.2018.00061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Software Reliability Model Based on Improved Bp Neural Network
Neural network has good fault-tolerant ability, classification ability, parallel processing ability and so on, so the research of software reliability model based on neural network is paid more and more attention. Bp neural network has strong nonlinear mapping ability and flexible network structure, so BP neural network is currently used in various fields. In this paper, a software reliability model optimized by hidden layer BP neural network is proposed and the training process of BP algorithm on this model is described.