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Applied research of combinatorial prediction model on the GMDH
基于GMDH的组合预测模型应用研究

Keywords: Group Method of Data Handle (GMDH) model,Analog Complexing (AC) model,combinatorial prediction,industry increasing value
数据处理的分组方法模型
,相似体合成算法模型,组合预测,工业增加值,GMDH,线性组合预测模型,应用,研究,prediction,model,combinatorial,预测能力,拟合精度,数据样本,改善,分组方法,验证,最优,工业增加值,回归算法,多层算法,数据处理

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Abstract:

Making use of Group Method of Data Handle (GMDH) multilayer model, GMDH self-regression model, multi-dimension 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.

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