计算机与数字工程2017，Vol.45Issue(12)：2465-2469,5.DOI:10.3969/j.issn.1672-9722.2017.12.029
基于树增强朴素贝叶斯分类器的出租车制动系统安全状态预测
Prediction of the Working Condition of Taxi's Braking System based on Tree Augmented Naive Bayesian Classifier
摘要
Abstract
The malfunction of the braking system is a main cause of the taxis'accidents on the road，therefore，predicting the working condition of taxi's braking system is meaningful for the management and maintenance on the taxis，reducing the casualty and economic losses caused by traffic accidents. This study is based on the database of 335 cases which is extracted from one of the Hefei Motor Vehicles Safety Technology Inspection stations. Based on three basic vehicle parameters-age，brand and weight，this study builds Tree Augmented Naive Bayesian Classifier（TAN）model，Decision Tree（DT）model and K Nearest Neighbors（KNN） model to predict the working condition of taxi's braking system. The results show that the TAN model outperforms the other two models with higher accuracy，sensitivity and specificity，thus with a good performance the proposed TAN model can be employed to pre-dict the working condition of taxi's braking system usefully.关键词
树增强朴素贝叶斯/出租车制动系统/安全状态Key words
tree augmented naive bayesian classifier(TAN)/taxi's braking system/working condition分类
信息技术与安全科学引用本文复制引用
程锦宝,石琴,陈一锴,丁晶晶..基于树增强朴素贝叶斯分类器的出租车制动系统安全状态预测[J].计算机与数字工程,2017,45(12):2465-2469,5.基金项目
安徽省科技攻关计划项目(编号:1501b042211)资助。 （编号:1501b042211）
