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基于组合预测模型的上海物流需求预测

Shanghai Logistics Demand Forecast Based on Combination Forecasting Model
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摘要 随着物流行业的快速发展,为保证资源配置的合理运用,提前预测地区的物流货运量情况必不可少。以上海为例,将灰色预测模型与三次指数平滑预测模型结合起来,利用方差倒数加权法得到系数,再根据上海2016年到2020年实际货运量建立组合预测模型,从而预测出上海未来十年的货运量。最终发现上海货运量呈现逐年增长趋势,并在2032年达到最高444543.15万吨。最后,依据预测的结果对上海物流发展提供一些建议。 With the rapid development of the logistics industry,it is essential to predict the logistics freight volume of the region in advance to ensure the reasonable utilization of resource allocation.Taking Shanghai as an example,the grey prediction model is combined with the cubic exponential smoothing prediction model,and the coefficient is obtained using the inverse variance weighting method.Then,a combination prediction model is established based on the actual freight volume of Shanghai from 2016 to 2020,in order to predict the freight volume of Shanghai in the next decade.Finally,it was found that the freight volume in Shanghai showed an increasing trend year by year,reaching a maximum of 444543.15 million tons in 2032.Finally,based on the predicted results,provide some suggestions for the development of logistics in Shanghai.
作者 盛俊凡 张志清 SHENG Junfan;ZHANG Zhiqing(School of Management,Wuhan University of Science and Technology,Wuhan 430081,China)
出处 《物流科技》 2024年第19期28-32,共5页 Logistics Sci Tech
基金 武汉科技大学“十四五”湖北省优势特色学科(群)项目“数字化转型背景下数据驱动的敏捷协同创新理论与方法研究”(2023D0402)。
关键词 物流需求 灰色预测模型 三次指数平滑预测模型 组合预测模型 logistics demand grey prediction model triple exponential smoothing prediction model combination prediction model
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