计算机应用 ›› 2012, Vol. 32 ›› Issue (09): 2628-2630.DOI: 10.3724/SP.J.1087.2012.02628

• 典型应用 • 上一篇    下一篇

基于关联面积法的物流货运量组合预测模型

周程1*,张培林2   

  1. 1.湖北经济学院 物流与工程管理学院,武汉 430205;
    2.武汉理工大学 交通学院,武汉 430063
  • 收稿日期:2012-03-19 修回日期:2012-04-28 发布日期:2012-09-01 出版日期:2012-09-01
  • 通讯作者: 周程
  • 作者简介:周程(1978-),女,湖北宜昌人,讲师,博士,主要研究方向:物流规划与管理; 张培林(1955-),男,湖北汉川人,教授,博士生导师,主要研究方向:交通与物流系统规划及管理。
  • 基金资助:

    教育部人文社科青年基金资助项目(12YJC630292);湖北省教育厅人文社会科学研究项目(2012Q099);湖北物流发展研究中心项目(2011A11)

Adaptive combination forecasting model for logistics freight volume based on area correlation method

ZHOU Cheng1*,ZHANG Pei-lin2   

  1. 1.School of Logistics and Engineering Management,Hubei University of Economics,Wuhan Hubei 430205,China;
    2.School of Transportation,Wuhan University of Technology,Wuhan Hubei 430063,China
  • Received:2012-03-19 Revised:2012-04-28 Online:2012-09-01 Published:2012-09-01
  • Contact: Cheng ZHOU

摘要: 针对物流货运量组合预测模型中赋权策略这个难点问题,在灰色模型、三次多项式趋势外推模型(PTEM)和三次指数平滑模型(TESM)基础上,引入关联面积法确定组合权系数,构建物流货运量组合预测模型。实例表明,与等权法、熵权法、平均绝对误差法对比分析可知,关联面积法综合体现了模型预测结果与真实时间序列之间的相关性及拟合误差,提高了模型预测性能和精度,是一种有效的组合赋权策略。

关键词: 组合预测, 关联面积法, 灰色模型, 组合权值, 物流

Abstract: The forecasting performance of combined model is typically influenced by the combination weights assignment. A new combination weights assignment approach based on area correlation method was proposed. This study applied grey model, Polynomial Trend Extrapolation Model (PTEM) and Triple Exponential Smoothing Model (TESM) to develop a combination forecasting model to predict logistics freight volumes, in which the coefficients of combination weights were determined by area correlation method. The new method based on area correlation method shows its superiority in determining combination weights, compared with some other combination weight assignment methods such as equal weight method, entropy weight method and reciprocal of mean absolute percentage error weight method. Since area correlation method can comprehensively evaluate both the correlation and fitting error of forecasting model, it is an effective approach to determine the combination weights.

Key words: combination forecasting, area correlation method, grey model, combination weight, logistics

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