Research on Prediction Method of Flight Guarantee Sorties and Prediction of Recovery Period
In order to study the future recovery and development of flight guarantee sorties,this paper introduces support vec-tor machines(SVM)based on traditional time series forecasting methods to optimize,and then predicts and judges future growth based on the impact of the COVID-19 epidemic,which provides some reference for the recovery of air transportation in the future.Firstly,based on two combined models of ARIMA-SVM and Holt-Winters three-parameter exponential smoothing-SVM,the accu-racy of the model is optimized based on no epidemic data.Then by using X-12 to decompose epidemic time series,this study pre-dicts the monthly value within 2021-2023,and judges the annual growth recovery.The results show that using SVM to optimize the residual sequence,the error is reduced compared with the single model.Through the analysis of the epidemic impact,it can be judged that the flight guarantee sorties under the influence of the epidemic is expected to return to the level before the epidemic in 2023.
flight guarantee sortiestime series forecastingARIMA multiplication seasonal modelHolt-Winters three-pa-rameter exponential smoothingrecovery period prediction
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