北京交通大学学报2017，Vol.41Issue(2)：54-58,5.DOI:10.11860/j.issn.1673-0291.2017.02.009
生产制造企业网络智能故障诊断算法
Algorithm of intelligent fault diagnose technology for network of manufacturing enterprise
摘要
Abstract
An intelligent fault diagnose algorithm(Classified Sample Random Forest,CSRF) is proposed according to the characteristics of manufacturing enterprise network.The algorithm combines the basic principle of random forest algorithm,using classified sampling technology to generate the required training samples,and largely solved the problem caused by data imbalance.The algorithm can generate the corresponding training data for each classification and regression tree (CART) in random forest,which alleviates the sampling bias and improves the performance of the algorithm.Experiments show that the algorithm improves the accuracy rate by about 4％ compared with the random forest algorithm,and reduces the risk of fault diagnosis effectively.关键词
工业以太网/智能算法/采样算法/随机森林Key words
industrial ethernet/intelligent algorithm/sampling algorithm/random forest分类
信息技术与安全科学引用本文复制引用
李红辉,赵京京,杨芳南..生产制造企业网络智能故障诊断算法[J].北京交通大学学报,2017,41(2):54-58,5.基金项目
国家科技支撑计划项目(2015BAF08B02,2015BAG12B00)National Key Technology Research and Development Program of China(2015BAF08B02,2015BAG12B00) （2015BAF08B02,2015BAG12B00）
