Research On Strategic Forecasting Techniques Of National Air Traffic Flow

The strategic forecasting technology of air traffic flow aims at analyzing the overall growth trendand its space-time distribution of future air traffic flow. This technology helps to explore thecontradictions of NAS. Moreover, it also helps us to develop Chinese civil aviation transportationindustry and provides the important bases of decision making of effective implement of strategic airtraffic management.Based on the existing research results, the model founded in this paper which is suitable forstrategically forecasting the air traffic volume by analyzing air traffic volume data is based on the greysystem theory, the multiple linear regression method, the system dynamics simulation technique, andthe existing air traffic volume strategic forecast research. Besides, depending on the historical data, itcombines grey system theory and regression model, describes the total trend of national air trafficvolume by using regression model, and modifies the change trend of air traffic volume by using greysystem theory and puts forward the combination forecast model of grey regression. Above all, basedon various influencing factors of air traffic volume, we analyze the importance level analyzed by greycorrelation, taking both advantages and disadvantages of multiple linear regression model and greyDGM model into consideration. This paper not only takes the lead in establishing a system dynamicssimulation forecast model which is geared to the air traffic volume forecasting, but also proposes thatin order to better provide scientific references for the air traffic volume management in China, weshould make best use of the advantages and bypass the disadvantages of every forecast method, makea combination forecast of both the forecast methods, and verify and supplement the strategic forecastof air traffic volume. According to the research, the method put forward in this paper can prejudge thedevelopment trend of air traffic flow and get better precision results which can better providescientific references for the air traffic volume management in China.