{"title":"一种改进的贝叶斯网络推理算法","authors":"Xiaodan Zhang","doi":"10.1109/ICINIS.2010.183","DOIUrl":null,"url":null,"abstract":"In the on-line fault diagnosis of auto engineer before factory in FAW, we adopt Bayesian network inference to get diagnosis result. To reduce inference complexity, an improved Bayesian network inference algorithm is presented based on graph search strategy under Martelli standard. Through proof, the complexity of the improved algorithm can reduce from exponential level to polynomial level. In experiment, the algorithm has been realized and been compared with expert system method, the experiment shows that the improved algorithm can improve the diagnosis efficiency. The algorithm has been applied in the on-line fault diagnosis of auto engineer before factory in FAW successfully.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Improved Bayesian Network Inference Algorithm\",\"authors\":\"Xiaodan Zhang\",\"doi\":\"10.1109/ICINIS.2010.183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the on-line fault diagnosis of auto engineer before factory in FAW, we adopt Bayesian network inference to get diagnosis result. To reduce inference complexity, an improved Bayesian network inference algorithm is presented based on graph search strategy under Martelli standard. Through proof, the complexity of the improved algorithm can reduce from exponential level to polynomial level. In experiment, the algorithm has been realized and been compared with expert system method, the experiment shows that the improved algorithm can improve the diagnosis efficiency. The algorithm has been applied in the on-line fault diagnosis of auto engineer before factory in FAW successfully.\",\"PeriodicalId\":319379,\"journal\":{\"name\":\"2010 Third International Conference on Intelligent Networks and Intelligent Systems\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Conference on Intelligent Networks and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINIS.2010.183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2010.183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In the on-line fault diagnosis of auto engineer before factory in FAW, we adopt Bayesian network inference to get diagnosis result. To reduce inference complexity, an improved Bayesian network inference algorithm is presented based on graph search strategy under Martelli standard. Through proof, the complexity of the improved algorithm can reduce from exponential level to polynomial level. In experiment, the algorithm has been realized and been compared with expert system method, the experiment shows that the improved algorithm can improve the diagnosis efficiency. The algorithm has been applied in the on-line fault diagnosis of auto engineer before factory in FAW successfully.