一种改进的贝叶斯网络推理算法

Xiaodan Zhang
{"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}
引用次数: 1

摘要

在一汽汽车工程师出厂前在线故障诊断中,采用贝叶斯网络推理得到诊断结果。为了降低推理复杂度,提出了一种基于Martelli标准下的图搜索策略的改进贝叶斯网络推理算法。通过证明,改进算法的复杂度可以从指数级降低到多项式级。在实验中实现了该算法,并与专家系统方法进行了比较,实验表明改进后的算法能够提高诊断效率。该算法已成功应用于一汽汽车工程师的出厂前在线故障诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Bayesian Network Inference Algorithm
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信