基于BP神经网络的非线性组合预测模型在粮食物流需求预测中的应用

Application of nonlinear combination forecasting model based on BP neural networks in grain logistics demand

鉴于单项预测模型的局限性,在确定粮食物流需求量的基础上,建立了基于BP神经网络的非线性组合预测模型,并把这一模型应用于长春市粮食物流需求的预测。误差分析表明,该预测模型可以有效地提高粮食物流需求量的预测精度。

In view of the limitations in the single forecasting model,the nonlinear combination forecasting model for grain logistics demand was put forward based on the assured grain logistics demand volume.The model was verified using the data of the grain logistics demand volume of Changcbun.The analysis of eroneous results shows that it efficiently improves the precision for the grain logistics demand forecasting.