摘要
物流量是衡量地区经济发展的重要因素,准确的物流预测结果对物流产业的发展具有重大的指导作用.神经网络是重要的综合预测评价方法,在解决众多非线性问题时,对于由数据资料缺失造成的预测结果与真实结果相差较大的问题,可以最大限度的减小误差,增加预测准确性.本文针对城市经济与城市物流存在的内在关系,以青海省为例,根据青海省相关经济发展因素建立基于神经网络的"城市经济—物流需求"预测模型,对其城市物流量进行预测,对比预测结果与实际结果可知其误差小、可信度较高.最后,通过此方法预测得到了青海省未来五年城市物流量,具有较高的科学价值.
Logistics volume becomes a significant factor in measuring regional economic development.Logistics forecast showing more accurate results plays a significant guiding role in the development of the logistics industry.Neural networks are important comprehensive forecast evaluation methods,which can minimize errors and increase forecast accuracy with regard to big gaps between forecast results and actual results resulted from lack of data in solving many nonlinear problems.Aiming at internal relationship between urban economy and urban logistics and taking Qinghai Province as an example,the paper is designed to construct a neural network-based ＂urban economy-logistics demand＂forecast model in correspondence with relevant economic development factors in Qinghai Province in order to forecast its logistics volume.The comparison between forecast results and actual results indicates small errors and relatively high reliability.Finally,predicts urban logistics property of the next five years in Qinghai province through the method and high value.
出处
《青海师范大学学报（自然科学版）》
2017年第4期43-50,共8页
Journal of Qinghai Normal University(Natural Science Edition)
关键词
神经网络
预测
物流量
可信度
neural network
forecast
logistics volume
reliability
