巢湖学院学报Issue(3)：26-32,7.
基于支持向量机的汽车故障预测贝叶斯网络推理系统研究
RESEARCH ON BAYESIAN NETWORK INFERENCE SYSTEM BASED ON SUPPORT VECTOR MACHINE FOR THE PREDICTION OF VEHICLE FAULTS
摘要
Abstract
Compared with the traditional diagnosis of automobiles, the prediction of automobile faults realizes the analysis of the possibility the types of automobile faults in future based on the analysis of the data of vehicle running conditions, ensuring the safety of automobile driving. Through in-depth research on automobile fault types and characteristics, a system of the data-driv-en fault inference is designed based on the previous technological achievements of the fault prediction. Support vector machine (SVM) is used in this paper to complete the classification of different types of faults of automobiles. With the combination of Bayesian Reasoning Network, a comprehensive analysis of the current state of automobiles and the prediction of the possibility of different faults in future can be completed. Finally, with software programming, the prediction system of automobile faults can be realized.关键词
故障预测/支持向量机/贝叶斯网络/MFCKey words
fault prediction/support vector machine/Bayesian Network/MFC分类
数理科学引用本文复制引用
赵翠荣..基于支持向量机的汽车故障预测贝叶斯网络推理系统研究[J].巢湖学院学报,2015,(3):26-32,7.基金项目
安徽省省级质量工程项目(项目编号2013jyxm276)；安徽文达信息工程学院自然科学研究项目(项目编号XZR2014A01) （项目编号2013jyxm276）
