基于无偏灰色马尔科夫模型的农产品冷链物流需求预测——以运城市为例  

Prediction of Agricultural Cold Chain Logistics Demand Based on Unbiased Grey Markov Model--Taking Yuncheng City as an Example

作　　者：车丹丹 CHE Dandan(Yuncheng Vocational and Technical University,Yuncheng 044000,China)

机构地区：[1]运城职业技术大学,山西运城044000

出　　处：《物流科技》2025年第6期125-128,132,共5页Logistics Sci Tech

基　　金：山西省高等学校哲学社会科学研究项目“基于‘互联网+智慧’医药供应链协同进化研究”(2024W275)。

摘　　要：随着人们对食品质量要求的提高,冷链运输的作用也在日益凸显。为精准把握运城市冷链物流需求,研究采用定量法进行预测。通过对运城市2015—2023年的冷链物流需求进行分析,研究发现,灰色预测模型能揭示物流需求量的总体变化趋势,而结合马尔科夫模型进行优化后,预测结果与实际需求更为吻合了。据此,我们采用无偏灰色马尔科夫模型预测2024年运城市冷链物流需求,预测结果为794.73万吨,与近年来运城市冷链物流需求的增长趋势相符。With people's increasing demand for food quality,the role of cold chain transportation is becoming increasingly prominent.In order to better grasp the cold chain logistics demand of Yuncheng City,this study quantitatively predicts the cold chain logistics of Yuncheng City.Through the prediction and analysis of the cold chain logistics demand in Yuncheng from 2015 to 2023,it is found that the grey prediction model can predict the overall trend oflogistics demand,and using the Markov model for optimization,the prediction results can better fit the demand.Therefore,using an unbiased grey Markov model to predict the cold chain logistics demand in Yuncheng City in 2024,the final prediction result is 7.9473 million tons,which is in line with the development trend ofincreasing cold chain logistics demand in Yuncheng City in recent years.

关 键 词：GM(1 1)模型 马尔科夫模型 冷链物流需求 

分 类 号：F326.6[经济管理—产业经济] TP18[自动化与计算机技术—控制理论与控制工程]