基于时间序列模型的国内航空货运量组合预测

Combination Forecast of Air Cargo Volume in China Based on Time Sequence Model

为了预测未来几年国内航空货运量,以2001-2016年我国国内航空货运量的统计数据为基础,采用时间序列模型中的二次指数平滑法和灰色预测法建立单项预测模型,在此基础上以误差平方和最小为目标建立了组合预测模型。通过预测结果与实际数据相比较,计算平均绝对百分误差进行精度检验,结果表明组合预测模型有效可靠,具有较高的预测精度。以此方法预测了2017-2021年国内航空货运量,为航空公司及相关政府部门提供数据参考。

According to air cargo volume statistical data in China from the year 2001 to 2016,second exponential smoothing forecasting model and gray model are established separately. Aiming at the minimizing sum of error squares, combination forecasting model is established. Forecast results are compared with actual data, and mean absolute percentage error is calculated for precision verification. The results prove the effectiveness, reliability, and high precision of the combined forecasting model. The model is employed to forecast the air cargo volume in China from the year 2017 to 2021 to provide data reference for airlines and related government departments.