Short-term Airfare Prediction Based on SARIMA Model
In order to study the problem of short-term airfare prediction among airports in different cities,this paper classifies ticket data by OD,cabin type,and ticket purchase time,and constructs a SARIMA model based on different scenarios.It uses the data from the current time series to calibrate the parameters of the model,predict the ticket price for the next time series.Taking the airfare data from Beijing to Shanghai in July 2023 as an example,through four experimental scenarios and an improved Beijing Capital—Shanghai Hongqiao experimental scenario,it is found that the SARIMA model with different scenarios can accurately predict short-term airfare.
air transportationairfare predictiontime seriesshort-term airfare prediction
国家科技期刊平台
NSTL
万方数据
