基于随机森林算法的铁路货物运达时间预测研究

为更准确地预测铁路货物运达时间,运用Python,设计实现了基于随机森林算法的铁路货物运达时间预测模型。根据不同的车辆属性来预测车辆到达终点站的时长,将车辆的各种影响因素考虑进去,进行特征向量的计算,在行驶过程中不断修正误差,使得终到时间预测更为精确。以张兰—定边的货物运输为实例进行实验验证,准确率较高,具有推广应用价值。

Prediction of railway freight arrival time based on Random Forest algorithm

In order to predict the arrival time of railway freight more accurately, this paper used Python to implement the prediction model of railway freight arrival time based on random forest algorithm. According to different vehicle attributes, the paper predicted the time of vehicles arriving at the terminal, took into account the various factors of vehicles, calculated the eigenvector, and constantly corrected the error in the process of driving, so that the prediction time to the destination was more accurate. The Zhanglan–Dingbian freight transportation was taken as an example to verify the model. The verification results show that accuracy of the model is high, which has the value of popularization and application.