The decision tree was applied in the rail deformation detection in this paper.
本文把决策树应用到轨道故障的检测中。
The decision tree (or rules) used for rail deformation detection was generated by learning the train data.
通过对训练数据的学习，生成用于轨道故障判决的决策树(或者规则)。
A rail deformation detection algorithm based on multi-threshold feature extraction was presented in this paper.
本文提出一种基于多门限特征提取的轨道故障检测算法。
The waveforms 'amplitude character will be more distinct through accelerations 'feature extraction, and this is propitious to rail deformation detection.
对加速度进行特征提取，可以使得波形的幅度特征更加明显，有利于进行轨道故障的检测。
This paper mainly discusses how to build a decision tree of rail deformation detection by using C4.5 algorithm and how to make decision of the rail deformation by building decision tree.
文中主要讨论如何应用C4.5算法构造列车轨道故障检测的决策树以及根据生成的决策树实现轨道故障的判决。
This paper mainly discusses how to build a decision tree of rail deformation detection by using C4.5 algorithm and how to make decision of the rail deformation by building decision tree.
文中主要讨论如何应用C4.5算法构造列车轨道故障检测的决策树以及根据生成的决策树实现轨道故障的判决。
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