列车仿真技术中基于属性矩阵图的故障分析决策树算法
发布时间：2019-01-16 03:45
【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。
[Abstract]:According to the characteristics of train running big data, a decision tree algorithm based on attribute matrix graph is proposed. Based on the simulation data of a certain train, the concrete process of calculating attribute metric, building attribute matrix graph model and constructing decision tree is described in detail. From the fault analysis results of the decision tree algorithm, it can be seen that the decision tree algorithm based on attribute matrix graph can accurately classify and induce fault problems, and provide reliable basis for fault prediction.
【作者单位】： 中国铁道科学研究院通信信号研究所;
【分类号】：TP311.13;U279.3
本文编号：2409428
[Abstract]:According to the characteristics of train running big data, a decision tree algorithm based on attribute matrix graph is proposed. Based on the simulation data of a certain train, the concrete process of calculating attribute metric, building attribute matrix graph model and constructing decision tree is described in detail. From the fault analysis results of the decision tree algorithm, it can be seen that the decision tree algorithm based on attribute matrix graph can accurately classify and induce fault problems, and provide reliable basis for fault prediction.
【作者单位】： 中国铁道科学研究院通信信号研究所;
【分类号】：TP311.13;U279.3
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