Empirical Analysis On Influencing Factors Of Railway Passenger Volume And Demand Forecast

The analysis of influencing factors and demand prediction of railway passenger volume are two important aspects in the research.Due to its particularity and complexity,railway passenger transport is affected by many aspects,including economic policy,population,science and technology,energy level and national construction level.Since the development of railway passenger transport,a large number of historical data and materials containing important information have been accumulated,which can reflect the changing trend in the development of railway passenger transport in a more comprehensive way.Based on the actual passenger volume data of each historical year of railway passenger transport,the model can be established to forecast and analyze the demand variation trend of railway passenger volume,to improve the accuracy of pre-decision to a certain extent,and play an auxiliary role in railway construction and scheduling optimizationBased on the above,this thesis first explains the influencing factors of railway passenger volume and the background and significance of the research on passenger demand forecasting,and then sorts out the research methods,conclusions and results of domestic and foreign scholars in this field.The main chapter is divided into two parts,which are the empirical analysis of the influencing factors of railway passenger volume and the prediction and error analysis of the demand of railway passenger volumeIn the part of empirical analysis of the influencing factors of railway passenger volume,the index system is established by selecting the indexes from the aspects of economy,energy,population and the scale of railway,in turn,the grey correlation analysis method,through calculating correlation coefficient,the selected indicators and the connection degree of railway passenger traffic data,influence degree more indexes,combining economic sense,choose top four of the first industrial added value,economic activity in the population,the total energy consumption as well as the railway mileage four indicators for the establishment of the VAR model.Through unit root test,co-integration test and stationarity test to explore whether the model is reasonable,through Granger causality test,impulse response and variance decomposition to explore the relationship between railway passenger transport and its influencing factorsOf railway passenger traffic demand forecasting and error analysis part,mainly through stepwise regression,ridge regression and support vector regression three kinds of methods to forecast the annual data of railway passenger traffic,three kinds of regression model and calculate the error of the model are compared,and the precision research found that the support vector regression fitting and prediction effect is best,followed by ridge regression,stepwise regression accuracy compared with other two kinds of model precision is lowAt the end of this thesis,the empirical analysis of the influencing factors and the results of demand forecasting are sorted out,and the suggestions for the development of railway passenger transport are put forward,and the deficiencies and prospects of this paper are noted.