Forecasting of railway passenger flow based on Grey Model and monthly proportional coefficient

Abstract

Passenger departure volume is a vital index of railway station, which has very important significance to the organization station passenger transportation work. Aiming at the influences and characteristics of railway passenger flow, the Grey Model is applied to forecast annual passenger departure volume of railway station. Then, according to the fluctuating regularity of the passenger flow in each month, the monthly proportional coefficient method is used to predict passenger flow volume of each month. The case shows that the forecasting method putting forward in this paper has many advantages, such as low forecasting error, high accuracy, easy to calculate, and good maneuverability, and so on. It can supply accurate and reliable reference for the determination of railway station passenger transport plan and daily organization of passenger transport work, so as to assist decision-maker to make correct and reasonable decisions.