基于参数优化的物流需求灰预测研究  

Grey Forecast of Logistics Demand Based on Parameter Optimize Model

作　　者：田刚[1] 李南[2] 刘思峰[2] 

机构地区：[1]江苏大学工商管理学院,江苏镇江212013 [2]南京航空航天大学经济与管理学院,江苏南京210016

出　　处：《华东经济管理》2011年第6期155-157,共3页East China Economic Management

基　　金：国家自然科学基金资助项目(70473037)

摘　　要：在当前大力发展物流业的同时,需要做好物流需求预测,从而为各地科学合理地制定物流发展规划,实现物流系统供需平衡提供重要决策依据。物流系统是典型的灰色系统,文章利用江苏省物流货物周转量历史数据建立新陈代谢GM(1,1)模型群,并对模型参数进行优化,通过对模型群中不同维度的各个模型进行比较,选取其中精度较高的模型对货物周转量进行预测。结果表明模拟与预测效果均很好,模型有较高的应用价值。Logistics demand forecast is very important for development of the logistics industry,, which affects logistical development planning, and the balance between supply and demand of the logistics system. As logistics system is a typical gray system, this paper es- tablished metabolic GM （ 1, 1 ） model groups based on the historical data on freight mileage of Jiangsu province. After comparing the precision of the models with different dimensions, one of the model with higher accuracy is selected to predict freight mileage. The simulation and prediction results show that the model is valuable for logistics demand forecast.

关 键 词：货物周转量 新陈代谢GM(1 1)模型 参数优化 预测 

分 类 号：F273[经济管理—企业管理]