基于组合预测模型的水产品冷链物流需求预测研究——以江苏省为例  

Study on Demand Forecasting of Cold Chain Logistics for Aquatic Products Based on Combinatorial Predictive Model--A Case Study of Jiangsu Province

作　　者：柳德才[1] 周志杰 LIU De-cai;ZHOU Zhi-jie(School of Management,Wuhan University of Science and Technology,Wuhan 430000,China)

机构地区：[1]武汉科技大学管理学院,湖北武汉430000

出　　处：《物流工程与管理》2023年第10期4-8,共5页Logistics Engineering and Management

摘　　要：据国家统计局数据显示,我国水产品消费常年居于世界第一。面对不断攀升的水产品需求,准确预测其冷链物流需求量对于提高水产品冷链物流运输效率具有重要意义。文中以江苏省为例,采用MatLab2019a数据处理工具,分别运用指数平滑法、灰色预测模型以及基于指数平滑法和灰色预测的组合预测模型对比分析其水产品冷链物流需求量,目的在于考察这三种方法和模型中的哪一种预测精度更高。研究表明,基于指数平滑法和灰色预测的组合预测模型能有效地克服单个预测模型的不足,预测精度更高。According to data from the National Bureau of Statistics,China's consumption of aquatic products has been consistently ranked first in the world.Accurately predicting the demand for cold chain logistics is of importance significance for improving the efficiency of cold chain transportation of aquatic products,which is constantly increasing in demand.Taking Jiangsu Province as an example and using Matlab2019a data processing tool,this study compares and analyzes the demand for cold chain logistics of aquatic products using exponential smoothing method,grey forecasting model and a combined forecasting model based on exponential smoothing and grey forecasting.The purpose is to examine which of the three methods and models has higher accuracy in prediction.The results show that the combination of exponential smoothing and grey forecasting can effectively overcome the shortcomings of individual prediction models and has higher prediction accuracy.

关 键 词：冷链物流 需求预测 指数平滑法 灰色预测模型 组合预测模型 

分 类 号：F252.1[经济管理—国民经济]