GMDH参数模型的改进及在煤炭价格研究中的应用

首先,针对现有GMDH算法的不足做了两点改进:一是利用初始变量添加法来防止有用信息丢失、改善模型结构、提高模型精度,二是用权系数向量法或符号表达式法直接给出GMDH输出的显式表达式;然后,将改进的GMDH算法应用于煤炭价格影响因素的实证研究。结果显示改进的GMDH算法能够更真实地反映实际的煤炭价格模型结构,不仅有更高的拟合精度,而且有良好的外推能力,能够准确预测煤炭价格的变动趋势。

Improvement of GMDH Parametric Modeling and Its Application to Coal Price Research

An improved GMDH modeling algorithm is presented to overcome the shortcomings of the existing GMDH algorithms in the constructing of partial polynomials and the explicit output expression of GMDH network.The input variables(i.e.,the first layer nodes) are always included in the candidate pool of the partial polynomials for determining the construcution of the higher layers,which can prevent the loss of useful information,simplify the model structure and improve the model’s performance.Furthermore,the weight coefficient method or the symbolic expression method is used to obtain the explicit output expression of GMDH network directly.The improved GMDH algorithm is then applied to the case study of coal price in China.The results show that the obtained GMDH model can reflect the actual coal price model structure with high fitting precision.Meanwhile,it can predict accurately the changing tendency of coal price,indicating that the model has good trend extrapolation ability.