基于GMDH的组合预测模型应用研究

Applied research of combinatorial prediction model on the GMDH

应用数据处理的分组方法(GMDH)多层算法、GMDH自回归算法、多维AC算法、单维AC算法,建立了基于GMDH的工业增加值预测模型,在此基础上建立了最优线性组合预测模型。实验证明本文方法不仅改善了模型对数据样本的拟合精度,而且提高了模型的预测能力。

Making use of Group Method of Data Handle （GMDH） multilayer model, GMDH self-regression model, multidimension AC model and single dimension Analog Complexing （AC） model, a prediction model for industry increasing value based on the GMDH was established. Furthermore, an optimal linear combinatorial prediction model was also built up. Experimental results show that this prediction model can not only improve simulation precision of the model, but also evidently improve the prediction ability of the model.