海口港水产品冷链物流需求预测研究  

Research on Demand Prediction of Cold Chain Logistics for Aquatic Products in Haikou Port

作　　者：李芸嘉 张修志 Li Yunjia;Zhang Xiuzhi(Hainan College of Economics and Business,Haikou 571100,Hainan)

机构地区：[1]海南经贸职业技术学院,海南海口571100

出　　处：《中国商论》2024年第8期87-90,共4页China Journal of Commerce

基　　金：2023海南省高等学校科学研究重点项目“‘双循环’新发展格局下我国自由贸易区物流高质量发展问题研究”(Hnky2023ZD-20);海南经贸职业技术学院横向课题“琼蒙两省食品冷链物流发展现状比较”(hnjmhx2023003);海南经贸职业技术学院横向课题“海南物流地产发展报告”(hnjmhx2023002)。

摘　　要：本文主要探讨海口港水产品冷链物流需求预测的方法和应用。海口港作为海南主要港口,其水产品冷链物流需求预测具有重要的现实意义。本文首先介绍SVM支持向量机和BP神经网络两种预测方法,其次通过对比分析,选择BP神经网络作为预测模型,最后以海口港为例,运用BP神经网络模型对水产品冷链物流需求进行预测,并提出了相应的优化建议。本文的研究结论可以为相关企业和部门提供决策参考,以期促进海口港水产品冷链物流的持续发展。This paper aims to explore the methods and applications of predicting the demand of cold chain logistics for aquatic products in Haikou Port.As Haikou Port stands as a main port in Hainan Province,the demand prediction of cold chain logistics for aquatic products in this port has important practical significance.This paper begins by introducing two prediction methods,namely support vector machine(SVM)and BP neural network,and then selects BP neural network as the prediction model through comparative analysis.Finally,taking Haikou Port as an example,this paper uses the BP neural network model to predict the demand of cold chain logistics for aquatic products and gives corresponding optimization suggestions.The research in this paper can provide decision-making references for relevant enterprises and departments,promoting the sustainable development of cold chain logistics for aquatic products in Haikou Port.

关 键 词：SVM BP神经网络 海口港 冷链物流 需求预测 物资流通 水产品 

分 类 号：F252[经济管理—国民经济] F762.6