Freight traffic of civil aviation volume forecast based on hybrid ARIMA-LR model

Abstract

Freight traffic of civil aviation has developed rapidly because of its advantages of fast transportation speed and high safety. The fluctuation of freight traffic of civil aviation has brought many challenges to air traffic scheduling. If the freight traffic of civil aviation volume can be accurately predicted, the difficulty of air traffic scheduling will be reduced and the transportation efficiency of air cargo will be improved. The current prediction model can’t properly respond to the impact of emergencies. And it is not sensitive to the trend variations caused by policies, epidemics and other factors. In this paper, based on the autoregressive integrated moving average model (ARIMA) and linear regression model (LR), a hybrid ARIMA-LR model is proposed by using an improved Bayesian combined model. Through the prediction of the actual freight traffic of civil aviation volume, it is found that the hybrid ARIMA-LR model can not only better adapt to the changes caused by emergencies, but also have higher overall prediction accuracy than the ARIMA model and LR model. The three indicators of mean absolute error (MAE), mean square error (MSE) and mean absolute percentage error (MAPE) of the hybrid ARIMA-LR model are 1.06,29.02,0.03 lower than that of the ARIMA model; compared with the LR model, it is reduced by 3.00,92.00,0.06.