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基于时间序列的上海市物流需求预测分析 被引量:2

Analysis on Shanghai Logistics Demand Forecast Based on Time Series
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摘要 文章通过收集近十年上海市的货运周转量及可能影响物流产业发展的相关经济指标数据,归纳总结以往学者对物流需求预测的必要性,运用线性回归法和指数平滑法对上海市的物流需求进行预测,通过对比分析选取基于时间序列的指数平滑法的预测结果,对上海市的物流业发展水平做了定量估计,为上海市物流产业的发展提供对策,助力上海市成为“十四五”规划中长三角世界级城市群的核心引领者,实现物流产业现代化。 By collecting the freight turnover of Shanghai in recent ten years and related economic index data that may affect the development of logistics industry,this paper summarizes the necessity of logistics demand prediction of previous scholars,and uses linear regression method and exponential smoothing method to forecast the logistics demand of Shanghai.Through comparative analysis,the prediction results of exponential smoothing method based on time series are selected.The paper makes a quantitative estimation of the development level of logistics industry in Shanghai,provides countermeasures for the development of logistics industry in Shanghai,and helps Shanghai become the core leader of world-class urban agglomeration in Yangtze River Delta in the 14th Five-Year Plan( 2021—2025),and realize the modernization of logistics industry.
作者 王胜源 朱芷童 WANG Shengyuan;ZHU Zhitong(School of Business Management,Liaoning Technical University,Huludao 125105,China)
出处 《物流科技》 2022年第18期50-54,共5页 Logistics Sci-Tech
基金 2018年度教育部人文社会科学研究青年基金项目(18YJC860032)。
关键词 物流工程 物流预测 线性回归法 指数平滑法 “十四五”规划 logistics engineering logistics forecast linear regression method exponential smoothing method 14th Five-Year Plan
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