Passenger flow forecast model for intercity high speed railway - A neural network-based analysis

Intercity high speed railway play an important role for the future development of urban agglomeration, this paper proposes to use Neural Network model to forecast the passenger flow for intercity high - speed railway, puts forward the method of combining the current policy with the time of forecasting the special traffic, and then establishes a new process to forecast the intercity high-speed railway passenger flow with combining quantitative and qualitative approach. By the empirical analysis of Beijing Nan Station, this paper verifies the feasibility and accuracy of the model. The new forecasting process enriches the existing research on the forecast of passenger flow and has a good reference for analyzing trends and seasonal characteristics for intercity high speed railway.