计算机工程与应用2019，Vol.55Issue(4)：185-192,8.DOI:10.3778/j.issn.1002-8331.1708-0032
SL-SMOTE和CS-RVM结合的电子设备故障检测方法
Fault Detection Method of Electronic Equipment Based on SL-SMOTE and CS-RVM
摘要
Abstract
Aimming at the problems of complicated mechanism of fault and lack of faulty samples in fault detection of electronic equipment, a fault detection method based on Safe Level Synthetic Minority Oversampling TEchnique (SL-SMOTE)and Cost Sensitive Relevance Vector Machine(CS-RVM)is proposed. The proposed method considers the fault detection of electronic equipment as an imbalanced binary-class classification problem. Firstly, SL-SMOTE is used in data layer to expand the fault samples. Then RVM detector is trained by these optimized samples. At last, cost sensitive learning is introduced to the detection in order to get the results at the minimun cost of loss. The experimental results of the UCI dataset and application case show that the proposed method effectively improves the detection accuracy.关键词
故障检测/非平衡数据/过采样/代价敏感/相关向量机Key words
fault detection/ imbalanced data/ oversampling/ cost sensitive/ relevance vector machine分类
信息技术与安全科学引用本文复制引用
高明哲,许爱强,许晴..SL-SMOTE和CS-RVM结合的电子设备故障检测方法[J].计算机工程与应用,2019,55(4):185-192,8.基金项目
国家部委预研基金. （）
