组合预测模型在黑龙江省农机总动力预测中的应用

农机总动力是反映和评价农业机械化水平的一个重要指标.通过对黑龙江省农机总动力历史数据进行分析,建立了指数模型、GM（1,1）模型和BP神经网络模型3种预测模型,其次,应用基于离异系数法、二次规划法、Shapley值权重分配法分别构建组合预测模型.拟合结果表明,各种组合预测模型优于各单一模型.最后应用基于Shapley值权重分配法对黑龙江省农机总动力进行组合预测,为制定农机动力发展规划提供了依据.

The Application of Combination Forecasting Model in Heilongjiang Agricultural Machinery Total Power Prediction

Agricultural machinery total power is an important index to reflect and evaluate the level of agricultural mechanization.Firstly,we respectively made use of exponential model,grey forecasting and BP neural network to construct models depending on historical data of agricultural machinery total power of Heilongjiang Province ; Secondly,we constructed the combined forecasting models that respectively based on divergence coefficient method,quadratic programming and weight distribution of Shapley value.Fitting results showed that the various combination forecasting model is superior to the single models.Finally,we applied the combination forecasting model which based on the weight distribution method of Shapley value to forecast Heilongjiang agricultural machinery total power,and it would provide some reference to the development and program for power of agriculture machinery.