Description

Passenger train delay significantly influences riders’ decision to choose rail transport as their mode choice. This article proposes real-time passenger train delay prediction (PTDP) models using machine learning techniques. This system is, to improve the accuracy of predicting train arrival delay time is of great significance for improving airport transportation efficiency. In our process, we have to take the input as time series dataset. After that, we have to implement the machine learning algorithms such as logistic regression and random forest. The experimental results shows that the accuracy and error values for each algorithm. The model has good prediction accuracy and can track the trends of multiple delay indicators well.