Research Of Short-term Passenger Transportation Volume Forecasting Methods

Railway passenger transportation volume forecasting is an important basis of passenger traffic organizing and an effective way for the passenger traffic enterprise to grasp the trends and demand of transportation market development.This paper focuses on short-term passenger volume forecasting problem. The objective is to investigate appropriate forecasting methods in order to guarantee the precision.This paper begins the research work from observing the fluctuation characteristics of short-term passenger railway volume, and finds some special properties of the volume change. On this basis, the paper gives a conclusion that methods based on time series analyzing should be used in short-term passenger volume forecasting.Then proceeding from request for short-term passenger volume forecasting, the paper proposes three single methods, which are seasonal adjustment method, Box-Jenkins method and gray prediction method and also analyzes their advantages, disadvantages and different application conditions.Meanwhile, making use of the favorable specific property that combined models may put forward to the forecasting system, the paper sets up tentatively an combined forecasting methods based on the ANN theory which may accord with the short-term passengers volume forecasting, which has been testified to be workable and more accurate than those single predicting methods.In order to observe the validity of method that the paper puts forward, the paper combines traditional forecasting methods and ANN theory, and the methods are applied to the actual monthly data of passengers of a section in an eastern line.