基于BP神经网络的云南花卉物流需求预测  

Demand Prediction of Yunnan Flower Logistics Based on BP Neural Network

作　　者：贺梦桐 张凌[1] HE Mengtong;ZHANG Ling(Wuhan University of Science and Technology,Wuhan 430065,China)

机构地区：[1]武汉科技大学,湖北武汉430065

出　　处：《物流科技》2024年第1期63-66,共4页Logistics Sci-Tech

摘　　要：文章首先对云南花卉市场进行现状分析,在此基础上以近10年来云南花卉总产值为变量依据,来预测云南花卉的未来物流需求量情况。文章提出了可能会影响花卉物流需求量的8个因素,运用BP神经网络预测法并结合近10年的云南花卉总产值对未来3年的需求量进行预测。预测结果表明,未来几年,云南花卉市场对于物流的需求不降反增。而作为鲜活植物产品,花卉的运输又对冷链物流提出了更高的要求。因此,提高冷链物流的技术势在必行。The paper first analyzes the current situation of Yunnan flower market,and on this basis,based on the total output value of Yunnan flowers in the past decade,to predict the future logistics demand of Yunnan flowers in the past 10 years.This paper puts forward 8 factors that may affect the demand of flower logistics,and predicts the demand in the next three years with the BP neural network prediction method and the total output value of Yunnan flowers in the past 10 years.The forecast results show that in the next few years,the demand for logistics in Yunnan flower market will increase rather than decrease.As a fresh plant product,the transportation of flowers has put forward higher requirements for the cold chain logistics.Therefore,it is imperative to improve the improvement of cold chain logistics technology.

关 键 词：云南花卉 BP神经网络预测法 物流需求 冷链物流 

分 类 号：F253[经济管理—国民经济]