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变权组合预测模型下的武汉港物流需求预测研究

Wuhan Port Logistics Demand Forecasting Study under Variable Weight Combination Forecasting Model
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摘要 武汉港作为我国中部地区最重要的交通枢纽之一,对我国港口物流发展具有极其重要的影响,而对武汉港的货物吞吐量进行物流需求预测是其物流发展规划的重要组成部分。文章以单项预测模型为基础,将ARIMA模型、二次指数平滑法以及灰色预测模型组合起来,建立了变权组合预测模型进行物流需求预测。经过分析比较后,发现变权组合预测模型的合理性和预测准确度比单项预测模型更好。同时观察到武汉港未来的货物吞吐量将会稳中向好增长,并对武汉港物流发展提出相应的建议。 As one of the most important transportation hubs in the central region of China,Wuhan Port has an important impact on the development of port logistics in China,and logistics demand forecasting for the cargo throughput of Wuhan Port is an important part of its logistics development planning.Based on a single forecasting model,the article combines ARIMA model,quadratic exponential smoothing method and gray forecasting model,and establishes a variable-weight combination forecasting model for logistics demand forecasting.After analyzing and comparing,it is found that the rationality and prediction accuracy of the variable-weight combination prediction model is better than the single-item prediction model.Meanwhile,it is observed that the cargo throughput of Wuhan Port will grow steadily in the future,and corresponding suggestions are put forward for the logistics development of Wuhan Port.
作者 张潜卫 陆芬 ZHANG Qianwei;LU Fen(School of Management,Wuhan University of Science and Technology,Wuhan 430081,China;Center for Service Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China)
出处 《物流科技》 2024年第17期70-74,共5页 Logistics Sci Tech
基金 湖北省教育厅科学技术研究项目“考虑随机学习效应的双渠道供应链战略库存决策研究”(B2020005)。
关键词 港口物流预测 变权组合预测 ARIMA模型 灰色预测 二次指数平滑法 port logistics forecasting variable weight combination forecasting ARIMA model gray forecasting quadratic exponential smoothing method
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