基于滑动无偏灰色模型的湖南省农产品冷链物流需求预测  

Demand prediction on cold chain logistics of agricultural products in Hunan province based on a new dimension sliding unbiased grey model

作　　者：李义华 王冲 文哲 杜康 孙雅伦 尹楚萱 LI Yihua;WANG Chong;WEN Zhe;DU Kang;SUN Yalun;YIN Chuxuan(School of Transportation&Logistics,Central South University of Forestry&Technology,Changsha 410004,Hunan,China;Bangor College,Central South University of Forestry&Technology,Changsha 410004,Hunan,China;Hunan Hupingshan National Nature Reserve Administration Bureau,Changde 415300,Hunan,China;Hisense TansTech Network Technology Co.,Ltd,Qingdao 266071,Shandong,China)

机构地区：[1]中南林业科技大学物流与交通学院,湖南长沙410004 [2]中南林业科技大学班戈学院,湖南长沙410004 [3]湖南壶瓶山国家级自然保护区管理局,湖南常德415300 [4]海信网络科技有限公司,山东青岛266071

出　　处：《中南林业科技大学学报》2021年第8期161-168,共8页Journal of Central South University of Forestry & Technology

基　　金：湖南省社会科学基金项目(16YBA380);湖南省教育厅重点项目(16A225);智慧物流技术湖南省重点实验室项目(2019TP1015)。

摘　　要：【目的】冷链物流需求预测是经济区域冷链物流基础设施规划与相关政策制定的基础工作,建立区域农产品冷链物流需求预测分析框架、选择合适预测方法具有重要的现实意义。以冷链流通量作为度量指标,在传统灰色预测模型基础上构建了一种滑动无偏灰色预测模型对相关经济区域的冷链物流量进行预测。【方法】在传统灰色预测模型的基础上,构建了相应的滑动无偏灰色预测模型,以湖南省2009—2018年各主要农产品的年度生产总量作为原始数据,按照两种不同预测方法分别设计了拟合分组试验和预测分组试验,并采用相对误差α、均方差比值c、小误差概率p作为检验指标,比较分析了传统灰色预测模型和滑动无偏灰色预测模型的预测效果。在此基础上,依据冷链物流相关政策法规,设计了一种冷链物流需求量的分析预测框架,并利用2009—2018年湖南省各主要农产品年度生产总量作为初始数据,选用滑动无偏灰色预测模型对湖南省2019—2025年农产品冷链物流需求量进行了分析预测。【结果】分组试验结果显示,滑动无偏灰色模型的拟合效果与预测可靠性均要优于传统灰色预测模型,因此本研究选用滑动无偏灰色预测模型对湖南省2019—2025年的农产品冷链物流需求量进行预测更加合适有效;最终预测结果显示,湖南省“十四五”期间农产品冷链物流需求量将逐年增加,年均增长率将达到15.42%,并且随着冷链物流水平的不断提高,湖南省农产品冷链物流需求的增长速度也会逐渐放缓。根据湖南省经济社会发展具体情况,最后对湖南省的冷链物流发展及冷链设施规划提出了可供参考的对策建议。【结论】本研究为有关经济区域冷链物流需求预测提供了一种简便有效的办法,分析预测结果可以为湖南省冷链物流“十四五”规划提供参考。【Objective】Cold chain logistics demand forecast is the basic work of cold chain logistics infrastructure planning and related policy formulation in economic areas,and it is of great practical significance to establish a framework for the analysis of regional cold chain logistics demand forecasting and select appropriate forecasting methods.Based on the traditional grey prediction model,a sliding unbiased grey prediction model is constructed to predict the cold chain logistics volume in the relevant economic area.【Method】On the basis of the traditional grey prediction model,the corresponding sliding unbiased grey prediction model is constructed,taking the annual total production of major agricultural products in Hunan province from 2009 to 2018 as the original data,the fitting grouping experiment and the prediction grouping experiment are designed according to two different prediction methods,and the relative errorα,mean square error ratio c and small error probability p were used as the test index,the prediction effect of traditional grey prediction model and sliding unbiased grey prediction model is compared and analyzed.Meanwhile,On this basis,according to the relevant policies and regulations of cold chain logistics,a cold chain logistics demand analysis and forecasting framework is designed,and the annual production volume of major agricultural products in Hunan province from 2009 to 2018 is used as the initial data,the sliding unbiased grey prediction model is selected to analyze and forecast the demand of agricultural products cold chain logistics in Hunan province from 2019 to 2025.【Result】The results of the group test show that the fitting effect and prediction reliability of the sliding unbiased grey model are better than those of the traditional grey prediction model.Therefore,selecting the sliding unbiased grey prediction model is more appropriate and effective to predict the demand of cold chain logistics of agricultural products in Hunan province in 2019-2025.The final prediction results

关 键 词：农产品物流 冷链物流 需求量预测 滑动无偏灰色模型 湖南省 

分 类 号：S7-05[农业科学—林学] F252.8[经济管理—国民经济]