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新冠疫情下基于SARIMA模型的上海港集装箱吞吐量预测

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中国作为港口大国,上海港的集装箱吞吐量连续多年世界第一.2019年12月暴发的新冠疫情对世界航运造成了巨大影响,对上海港的影响程度及其集装箱吞吐量的未来走势亦未可知.因此,本文以上海港过去9年的集装箱吞吐量月度数据为原始样本,对上海港2022年11月至2023年10月的集装箱吞吐量进行预测.为排除季节效应,建立SARIMA模型进行时间序列分析,结果表明预测精度良好.另外,为减小疫情对未来预测值的影响,利用异常值替换法改进了基础模型,并选取最优模型对上海港未来集装箱吞吐量进行预测,结果可为行业人员制定作业计划与人员配备提供参考.
Data Forecast of Container Throughput in Shanghai Port Based on SARIMA Model Considering COVID-19
China is a major port country and Shanghai Port has long been the world leader in terms of container throughput.The COVID-19 epidemic in December 2019 had a significant influence on global shipping.But it is unclear how much it has affected Shanghai Port and what the future trends in container throughput will be.Therefore,to forecast the container throughput of Shanghai Port from November 2022 to October 2023,monthly data from the port's container throughput of the previous nine years were used as the original samples.A SARIMA model for time series analysis was conducted to eliminate the seasonal impacts.The results show that the forecast is accurate.Additionally,the base model was enhanced using the abnormal value replacement method to lessen the impact of the COVID-19 on the future data forecasts.The optimal model was chosen to forecast the throughput of containers at Shanghai Port.The findings demonstrate that industry managers can use the forecast data as a guide when developing relevant plans and staffing.

data forecastingSARIMA modelcontainer throughputCOVID-19

陈治霖、胡鸿韬、边迎迎

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上海海事大学物流工程学院,上海 201306

上海海事大学经济管理学院,上海 201306

数据预测 SARIMA模型 集装箱吞吐量 新冠疫情

国家自然科学基金面上项目

72271156

2024

工业工程与管理
上海交通大学

工业工程与管理

CSTPCD北大核心
影响因子:0.763
ISSN:1007-5429
年,卷(期):2024.29(1)
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