基于灰色马尔科夫模型江苏城镇农产品冷链物流需求量的预测

从江苏省城镇居民农产品冷链物流的需求状况作为研究点.以《江苏统计年鉴》2011-2019年的数据作为样本,选取了鲜菜,猪肉,鱼虾,鲜蛋,鲜奶,瓜果等影响因子,逐步缩小数据筛选范围.运用灰色GM(1,1)模型结合Matlab2017b软件对江苏省城镇居民未来五年冷链的需求量进行预测,预测模型结果表明精度为97.62％,并通过马尔科夫链进行优化,使预测的精度达到98.61％.实验结果给相应的部门提供数据借鉴,以期为促进农产品冷链的供需平衡提供理论支持.

Forecast of Cold Chain Logistics Demand of Agricultural Products in Jiangsu Based on Grey Markov Model

In order to study the demand of cold chain logistics of agricultural products of urban residents in Jiangsu Province, this paper takes the data of Jiangsu statistical yearbook from 2009 to 2017 as the sample, selects the influencing factors such as fresh vegetables, pork, fish and shrimp, fresh eggs, fresh milk, melon and fruit, gradually reduces the data range, and uses the grey GM (1,1) model and MATLAB 2017b software to predict the demand of cold chain in the next five years, The accuracy of the prediction model is 97.62%, and the prediction accuracy is 98.61% through the optimization of Markov chain. The experimental results show that the optimization of the gray Markov model can provide data reference for the corresponding departments through the prediction results, in order to promote the supply and demand balance of the cold chain of agricultural products to provide theoretical support.