Analysis and Forecast on Air Passenger Transport Market Demand Based on SARIMA-LSTM Model
Market demand forecast is the premise of airlines to carry out production activities.Scientif-ic and reasonable prediction results can reduce costs and improve efficiency for airlines.Firstly,the factors affecting the market demand of air passenger transportation are selected,and their relativities are analyzed accordingly.Then,the seasonal auto regressive integrated moving average(SARIMA)model and the long short term memory(LSTM)network model are used to analyze the characteristics of air passenger transport market demand.A combined forecasting(SARIMA-LSTM)model based on SARIMA model and LSTM network model is constructed to improve the accuracy of market de-mand time series forecast.Finally,taking the air transport market in Beijing as an example,the analy-sis results show that the SARIMA-LSTM combination model has a higher forecasting accuracy than the single model,and the forecasting accuracy of market demand is superior.
seasonal auto regressive integrated moving average(SARIMA)modellong short term memory(LSTM)network modelSARIMA-LSTM combination modeldemand forecast
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