列车仿真技术中基于属性矩阵图的故障分析决策树算法  

Application of Decision Tree Optimization Algorithm in Train Simulation Technology

作　　者：王超[1] 

机构地区：[1]中国铁道科学研究院通信信号研究所,北京助理研究员100081

出　　处：《城市轨道交通研究》2017年第12期97-99,共3页Urban Mass Transit

摘　　要：根据数据挖掘技术分析列车运行大数据的特点,提出了基于属性矩阵图的决策树算法。结合某列车仿真数据,详细阐述了计算属性度量、构建属性矩阵图模型及构造决策树的具体过程。由该决策树算法的故障分析结果可见,基于属性矩阵图决策树算法能准确地对故障问题进行分类归纳,为故障预测提供可靠依据。The data mining technology is used to analyze the large data generated during train operation,the decision tree algorithm is proposed based on attribute matrix graph. Combined with the simulation date of a train,the computing attribute matrix and the structure design of the decision tree optimization algorithm are elaborated. According to fault analysis result of the decision tree algorithm,this algorithm could classify the faults accurately and provide reliable basis for the prediction of metro faults.

关 键 词：属性矩阵图 决策树算法 列车仿真 故障分析 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] U279.3[自动化与计算机技术—计算机科学与技术]