Predicting passenger flow using different influence factors for Taipei MRT system

Abstract

Nowadays more and more people in the big city rely on public transportations while they go to work or school. MRT (Mass Rapid Transit) is one of the most modern transportations in Taipei. It is a great traffic tool to relieve the pressure of rush hours. According to the statistics, each day there will be over one million of passengers taking the MRT in Taipei. In this paper, we will be predicting MRT passenger flow with random forest, by using different factors collected from the Taipei Main station as input for training. The result shows that some of the influenced factors are important to affect the prediction of the passenger flow.