Indian Railways operates both long distance and suburban passenger trains and freight services daily in the country. Trains get delayed frequently due to several reasons such as, severe weather conditions such as fog, traffic, signal failure, derailing of trains, accidents, etc, and this delay is propagated from station to station. If we can predict this in advance - it would be of great help for the commuters to plan their journey either for an earlier departure or postpone, and also lets railways to take measures to avoid delays further. In this paper, we used decision tree, a machine learning method used for predicting train delays, and Recurrent Neural Networks distinguished with various fixtures. For predicting train delays, Recurrent Neural networks with 2 layers and 22 neurons per each layer gave best results with an average error of 122 seconds
Combining Stream Mining and Neural Networks for Short Term Delay Prediction
