Research On Forecast Of Passenger Throughput In Kunming Changshui International Airport Based On Grey Relational Theory

Civil aviation traffic is often planned and managed according to the forecast of civil aviation passenger throughput as routine work of civil aviation administrative organ normal.This paper analyzed the relevant influencing factors of civil aviation throughput the microscopic and macroscopic perspectives,expounds the characteristics and methods of passenger throughput prediction in civil aviation,based on the analysis of the development status of civil aviation passenger throughput in China.Finally,the paper compared and studied common forecasting methods in the world.Firstly,this paper illustrated the research significance,main contents and technical routes of passenger volume prediction,and then it introduced the grey theory,grey relational analysis method and grey prediction model,and this method has outstanding advantages of information shortage and solving unclear problems,which is consistent with the characteristics of civil aviation passenger data processing.It chosed the main factors that affect the civil aviation passenger volume by grey relational analysis method and predict the civil aviation passenger volume by grey prediction model.It was found that the model had some shortcomings that could not be ignored,which made the prediction error relatively larger.Through construct the weakening buffer operator,the Kunming Changshui International Airport(KMG)model that had been improved has been gotten.Through the empirical analysis toward the KMG civil aviation passenger volume,verifying the rationality of the passenger volume forecasting method proposed in this paper.Through the quantification prediction of the KMG civil aviation passenger volume,providing the basic data of extending study,providing basis for the effective allocation of resources.It also can avoid investment waste and overlapping investment and improve the operational efficiency service level of the KMG,providing some references for the prospects for development and strategic decisions.