基于灰色神经网络的长三角地区物流需求预测研究  

Research on Logistics Demand Prediction in the Yangtze River Delta Region Based on Gray Neural Network

作　　者：王艳 曹晗 WANG Yan;CAO Han

机构地区：[1]安徽理工大学经济与管理学院,安徽淮南232001 [2]淮南师范学院科研处,安徽淮南232038

出　　处：《淮南师范学院学报》2024年第5期44-54,共11页Journal of Huainan Normal University

基　　金：国家社会科学基金资助项目(20BGL85)。

摘　　要：区域货运量作为衡量区域物流需求的关键指标,其预测研究不仅揭示物流发展的规模,更反映物流业的未来趋势和发展方向。本研究以长三角地区为例,选取了物流需求的影响因素构建指标体系,利用灰色理论对长三角地区2001—2022年原始数据进行灰色关联分析及灰色预测;构建灰色神经网络模型,并对长三角地区2023—2027年的物流需求量进行预测分析。研究结果表明:灰色神经网络组合预测模型具有更高的精确性,预测结果可以为长三角地区物流的规划和发展提供一定的数据支持和决策参考。As a key indicator for measuring regional logistics demand,the prediction research of regional freight volume not only reveals the scale of logistics development,but also maps out the future trends and development directions of the logistics industry.This study takes the Yangtze River Delta region as an example and selects the influencing factors of logistics demand to construct an indicator system.Gray correlation analysis and gray prediction are conducted on the raw data of the Yangtze River Delta region from 2001to 2022using gray theory.Next,agray neural network model is constructed to predict and analyze the logistics demand in the Yangtze River Delta region from 2023to 2027.The research results indicate that the gray neural network combination prediction model has higher accuracy,and the prediction results can provide data support and decision-making references for the planning and development of logistics in the Yangtze River Delta region.

关 键 词：长三角地区 物流需求 灰色预测 BP神经网络 

分 类 号：F259.27[经济管理—国民经济]