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疫情影响下我国航空客运量恢复期预测
引用本文:赖颖.疫情影响下我国航空客运量恢复期预测[J].特区经济,2021(2):72-75.
作者姓名:赖颖
作者单位:浙江海洋大学港航与交通运输工程学院
摘    要:2020年爆发的新冠肺炎疫情给全国的经济社会带来了巨大的冲击。作为对非正常事件或危机事件高度敏感的航空客运业来说,经济损失更是巨大的。本文根据新冠肺炎疫情与航空旅客运输之间的影响机理,结合2009年至2020年间我国民航客运量的月度数据,运用复合型序列的分解预测模型,对正常运行情况下的航空客运量进行预测,再结合疫情影响下的航空数据进行对比分析。研究表明:2020年航空客运业由于疫情的影响,从1月到12月客运量至少减少15527万人;到年底,有望恢复上年同期航空客运量的90%以上。

关 键 词:疫情  分解预测模型  恢复期

Forecast of the Recovery Period of Air Passenger Volume in China under the Influence of Epidemic Disease
LAI Ying.Forecast of the Recovery Period of Air Passenger Volume in China under the Influence of Epidemic Disease[J].Special Zone Economy,2021(2):72-75.
Authors:LAI Ying
Institution:(School of Port And Transportation Engineering,Zhejiang Ocean University,316000,Zhoushan,Zhejiang,China)
Abstract:The outbreak of new coronary pneumonia in 2020 has brought great impact to the national economy and society. As a highly sensitive air passenger transport industry to abnormal events or crises, economic losses are even greater. According to the influence mechanism between the epidemic situation of Xinguan pneumonia and air passenger transport, combined with the monthly data of civil aviation passenger volume in China from 2009 to 2020, using the decomposition and prediction model of used to predict the air passenger volume under normal operation, and then the air data under the influence of epidemic situation are compared and analyzed. Research shows that the air passenger transport industry in 2020 due to the impact of the epidemic,from January to December lost at least 155.27 million passengers;by the end of this year, it is expected to restore more than 90% of air passenger traffic.
Keywords:epidemic situation  decomposition prediction model  recovery period
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