Prediction of Passenger Flow at Sanya Airport Based on Combined Methods
摘要：It is crucial to correctly predict the passenger flow of an air route for the construction and development of an airport. Based on the passenger flow data of Sanya Airport from 2008 to 2016, this paper respectively adopted Holt-Winter Seasonal Model, ARMA and linear regression model to predict the passenger flow of Sanya Airport from 2017 to 2018. In order to reduce the prediction error and improve the prediction accuracy at meanwhile, the combinatorial weighted method is adopted to predict the data in a combined manner.Upon verification, this method has been proved to be an effective approach to predict the airport passenger flow.
The Third International Conference of Pioneering Computer Scientists, Engineers and Educators,ICPCSEE 2017（originally ICYCSEE）