Influencing Factors And Forecasting Analysis Of Passenger Attendance Rate In China

With the gradual development of Chinese strategy from a big country of air transportation to a strong country of air transportation,the civil aviation industry becomes one of the most important strategic industries in the country,and it is an important part and a strong support for the construction of a strong transportation country.The passenger rate index is one of the important efficiency reference indexes of airlines.For airlines,the construction and development of the civil aviation industry need to focus on the passenger rate indicator,master its changing laws and influencing factors,it provides a better and faster guidance to the civil aviation power.Therefore,based on the daily high frequency data of an airline,this paper constructs models and algorithms,deeply explores the influencing factors of passenger attendance,and seizes the main factors to predict passenger attendance,so as to provide empirical support for the development policy of airlines.First of all,this article expounds the current situation of the development of the passenger rate of civil aviation in our country,we studied the daily high-frequency data of economy class and two-cabin passenger occupancy rate of an airline from 2010 to 2017,from which we obtained that the passenger occupancy rate data was affected by seasonality.Then,we focused on analyzing the daily high-frequency data of an airline's passenger attendance rate in 2017,it was verified from the two aspects of descriptive analysis and variance analysis that the difference in the region did cause differences in the passenger attendance rate;Therefore,we constructed the SVAR model to study the impact of this factor on passenger attendance from the regional differences,From this,we get the passenger rate data not only reflected in the influence on its own lag items,but also reflected in the lag items and the same period of other regions,indicating that regional differences have a real impact on the passenger rate.On the basis of this,it is found that the residual difference of passenger occupancy data in the Eastern,Central and Northeast regions has ARCH effect and its volatility is considered from the regional economic,and the GARCH model is established for data with fluctuating effects.The passenger attendance rate in the Northeast region will receive a positive impact,the passenger attendance rate will decrease.When receiving negative shocks,the passenger attendance level will increase.The forecast of passenger rate is an important basis for airline passenger transportation.In chapter 5,by deeply excavating the passenger attendance data of an airline in 2017,a multi-index random forest regression model including regional differences is established to predict the passenger attendance level,85.49 % of the training set was fitted,and the model fitted well,the mean square error RMSE is 0.0209447 by predicting the test set,which shows that the prediction accuracy is good and the model has no fitting phenomenon.At the same time,through the OOB residual mean square method,the factor of influence factor importance is evaluated,and it was analyzed that the regional difference index does have an impact on the passenger occupancy rate.The index that had the greatest impact on the passenger occupancy rate was the capacity index.At the end of this paper,we put forward some suggestions on the development of passenger attendance rate of civil aviation.