基于幂函数x-a变换的GM(1,1)模型在货运量预测中的应用研究
GM (1, 1) model based on power function x-a transformation and its application in freight volume forecasting

针对传统GM(1,1)模型对原始数列的光滑度要求较高且预测结果误差较大的问题,通过对原始货运量数据用幂函数x-a进行处理,将处理后的数据带入GM(1,1)模型进行预测,提出基于幂函数x-a变换的GM(1,1)货运量预测模型。最后,通过将该模型应用到实际案例中,验证基于幂函数x-a变换的GM(1,1)货运量预测模型较传统的GM(1,1)模型在预测精度方面有了较大幅度的提高,预测的相对误差降低了8.7%。研究结果表明,基于幂函数x-a变换的GM(1,1)模型可以更有效的对货运量进行预测。
In order to minis the excessive error and improve the smoothness of the sequence from traditional GM(1,1) mode in freight volume forecasting , this paper presents GM (1,1) freight volume forecasting model based on power function x-a transformation by using the power function x-a transformation to deal with the original freight volume data and bringing the processed data into the GM (1,1) model. Finally, by applying the model to the actual case, the model in forecasting accuracy has been significantly improved than traditional GM (1, N) model and the relative error of the prediction is reduced by 8.7%. It indicates that the GM (1,1) model based on power function x-a transformation can be more effective to forecast the freight volume