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

作　　者：鹿应荣[1] 杨印生[1] 刘洪霞[2] 

机构地区：[1]吉林大学生物与农业工程学院,长春130022 [2]吉林省农业科学院,吉林长春130033

出　　处：《吉林大学学报（工学版）》2008年第S2期61-64,共4页Journal of Jilin University:Engineering and Technology Edition

基　　金：吉林省国际合作项目(20060709);吉林省发展计划委员会高技术产业发展项目．

摘　　要：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.

关 键 词：交通运输系统工程 粮食物流 需求预测 非线性组合预测模型 BP神经网络 

分 类 号：F324.9[经济管理—产业经济]