灰色关联理论在物流成本预测中的应用  

Application of Grey Correlation Theory in Forecasting of Logistics Cost

作　　者：侯晓华[1] 

机构地区：[1]浙江东方职业技术学院,浙江温州325011

出　　处：《物流技术》2013年第5期293-295,共3页Logistics Technology

基　　金：教育部人文社会科学研究青年基金项目(11YJC630031);浙江省自然科学基金(Y6110042)的阶段性成果

摘　　要：为了对物流成本进行有效预测,以2000-2010年的物流成本数据为基础,分别采用灰色关联模型、基于最小二乘法的线性回归模型和时间序列模型对物流成本进行预测,并对预测结果进行了对比分析。结果表明,灰色关联预测模型的误差明显小于其他两种预测方法,预测精度最高,对物流成本的预测具有一定的理论价值和参考价值,在一定时期内可以为我国的宏观物流成本决策提供依据。In this paper, to forecast more effectively, with the logistics cost data of the years from 2000 to 2010 as the basis, we compared the grey correlation model, ｜east square linear regression model and time-series model in logistics cost forecasting as well as the forecasting results. We found that out of the three, the grey correlation forecasting model had markedly less error than the other two while boosting the highest forecasting accuracy.

关 键 词：灰色关联 物流成本 成本预测 线性回归模型 

分 类 号：F250[经济管理—国民经济]