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Airport passenger flow prediction based on various models

LIU Xia1, CHEN Lei1, QIU Zhao2, CHEN Huandong3, CHEN Mingrui2   

  1. (1. Academic Affairs Office, Sanya Aviation Tourism College, Sanya 572000, Hainan, China; 2. School of Information and Technology,Hainan University, Haikou 570228, China; 3. Academic Affairs Office, Hainan Normal University, Haikou 571158, China)
  • Received:2017-09-20 Revised:2017-11-19 Online:2018-06-24 Published:2018-06-26

Abstract: Based on the passenger flow data of Sanya Phoenix Internotional Airport (Sanya Airport for short) from 2008 to 2016, ARMA model, grey prediction GM (1, 1) model and improved ARMA regression model are adopted for data fitting. Upon verification, the average absolute percentage error of the three models are respectively 4.19%,
4.20% and 1.97% with high prediction precision. Passenger flow at Sanya Airport is predicted to reach 20 million in two years.

Key words: passenger flow, ARMA model, grey prediction model, RE-ARMA model