Evolution Pattern Discovery and Case Study of Logistics Companies Based on Time Series Analysis
Accurate demand forecasts are critical for logistics enterprises to improve the efficiency of their resource usage. Demand forecasts of logistics enterprises are closely related to the overall social environment, local economic development, related industries development, seasonal demand change, and the development of the enterprises. Therefore, a direct analytical model is difficult to obtain. Based on the analysis of the historical data of a typical shipping company, this paper presents a time series prediction model for logistics enterprises in the goods traffic forecasts, and through experimental analysis and comparison study, it found that the method proposed in this paper has higher prediction accuracy. Thus, the proposed model can be used to forecast the demand of the freight transport companies and has a spread value.
logistics demand forecasting time series analysis freight shipping companies GM(1,1) prediction
Bin Yang Xianbing Wu Zhihua Hu
Logistics Research Center, Shanghai Maritime University, Shanghai 200135 P. R. China
国际会议
2010 International Conference on Advanced Mechanical Engineering(2010年先进机械工程国际学术会议 AME 2010)
洛阳
英文
1099-1103
2010-09-04（万方平台首次上网日期，不代表论文的发表时间）