| 摘要: |
| 基于天猫“双十一”包裹量增长呈“Ｓ＂形和连续动态变化的特性，对“双十一”包裹量进行预测；首先将天猫历年“双十一”包裹量划分成几个连续区间，然后通过信息分解法对连续区间灰数进行白化处理，将区间灰数分解成白部序列和灰部序列，最后建立基于信息分解的连续区间灰数离散Verhulst预测模型；经误差检验分析，该模型预测结果精度较高，可以作为天猫平台第三方物流企业对物流资源进行合理、有效调配的依据。 |
| 关键词: 物流需求预测 信息分解 灰色离散Verhulst模型 “双十一包”裹量 误差检验 |
| DOI： |
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| Prediction of Tmall Double Eleven Logistics Demand Based on Interval Grey Number Prediction Model |
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ZHAO Xue qin,ZHANG Jun
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| Abstract: |
| Based on the characteristics of “S” and continuous dynamic changes in the growth of Tmall double eleven parcels，the amount of double eleven parcels is predicted First of all，Tmall double eleven package volume is divided into several continuous interval; then the continuous interval grey number is whitened by information decomposition method，and the interval grey number is divided into white and grey of part sequence;finally continuous interval grey number decomposition of discrete Verhulst prediction model is established to forecast the short term Tmall double eleven logistics demand The error analysis shows that the prediction accuracy of the model is relatively high，which can be used as a basis for rational and effective allocation of logistics resources on the third party logistics enterprises of Tmall platform |
| Key words: logistics demand forecast information decomposition grey discrete Verhulst model double eleven parcels error test |
