Abstract:
Load forecasting is a challenging problem and many Machine Learning approaches
have been used for the estimation of power consumption in the recent years. The
Indian Railways is a vast railway network. It is divided into 18 zones and each zone is
further divided into various divisions. The railway network is spread over a span of
1,21,407 kilometers all over the country. Due to the large spread of the railway
network in the country, it is a challenging problem to estimate the power consumption
for each zone. By applying a few traditional machine learning techniques such as
Linear Regression, Neural Networks and LSTM; we model the power consumption of
the Indian Railways. We further evaluate the performance of these models on real time
data of the power consumption of the Indian Railways in a certain spatio-temporal
zone.
