Optimal Weighted Combinatorial Forecasting Model In the Airport Cargo Prediction

According to the characteristics of the airport cargo, exponential curve model, unitary linear regression model and GM(1,1) model for the S individual airport cargo forecasts are conducted with good prediction, while the average absolute error of each model is no more than 5%. According to the criterion of minimizing the three single forecasting models' forecasting error sum of squares, we establish an optimal weighted combinatorial forecasting model, and use it to forecast the airport cargo with the average absolute error of only 1.73%, which further improves the predicting accuracy of the airport cargo.