Abstract: In this paper, a combined prediction model is proposed for the prediction of passenger reservation in civil aviation. First of all, according to the characteristics of reservation, this paper designs an algorithm dealing with missing values and noise so as to correct the reservation data effectively. Then, for improving prediction accuracy, a combined prediction model which is composed of the ARIMA and LSTM algorithm is constructed. The actual passenger reservation data of an airline company is used for the prediction. The experiments show that the values of MAE and RMSE of the combined model are smaller than single model before combination. The prediction result is also more accurate and applicable.

Key words: prediction model, autoregressive integrated moving average model, long short term memory network, combined model