A prediction model of China´s air passenger demand

In the process of the airlines´ demand management, air passenger demand prediction is an important basis for fleet investment and operating plan. This paper proposed a synthetic degree of grey incidence method to identify the key influencing factors of air passenger demand. With the key influencing factors, this method employed multiple regressions to reach satisfying prediction results. As a case study on the basis of GM(1,1) metabolic model, the proposed multiple regression model were used to predict China´s air passenger demand of the year from 2010 to 2014. The prediction results identified that China´s air passenger demand would still have rapid development in the next five years.