A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic

doi:10.1016/j.aei.2022.101678

	A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic
	Wang, Yue 1; Lv, Zhiqiang 1,2; Sheng, Zhaoyu 3; Sun, Haokai 3; Zhao, Aite 1
	2022-08-01
发表期刊	ADVANCED ENGINEERING INFORMATICS
ISSN	1474-0346
卷号	53 页码:12
摘要	The COVID-19 pandemic is a major global public health problem that has caused hardship to people's normal production and life. Predicting the traffic revitalization index can provide references for city managers to formulate policies related to traffic and epidemic prevention. Previous methods have struggled to capture the complex and diverse dynamic spatio-temporal correlations during the COVID-19 pandemic. Therefore, we propose a deep spatio-temporal meta-learning model for the prediction of traffic revitalization index (DeepMeta-TRI) using external auxiliary information such as COVID-19 data. We conduct extensive experiments on a real-world dataset, and the results validate the predictive performance of DeepMeta-TRI and its effectiveness in addressing underfitting.
关键词	Urban computing Traffic revitalization index prediction COVID-19pandemic Meta-learning Spatio-temporal correlation
DOI	10.1016/j.aei.2022.101678
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62106117] ; Shandong Provin-cial Natural Science Foundation, China[ZR2021QF084]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Multidisciplinary
WOS记录号	WOS:000841095600007
出版者	ELSEVIER SCI LTD
引用统计	被引频次：22[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/19453
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhao, Aite
作者单位	1.Qingdao Univ, Coll Comp Sci & Technol, Qingdao, Peoples R China 2.Inst Comp Technol, Chinese Acad Sci, Beijing, Peoples R China 3.Inst Ubiquitous Networks & Urban Comp, Qingdao, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yue,Lv, Zhiqiang,Sheng, Zhaoyu,et al. A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic[J]. ADVANCED ENGINEERING INFORMATICS,2022,53:12.
APA	Wang, Yue,Lv, Zhiqiang,Sheng, Zhaoyu,Sun, Haokai,&Zhao, Aite.(2022).A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic.ADVANCED ENGINEERING INFORMATICS,53,12.
MLA	Wang, Yue,et al."A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic".ADVANCED ENGINEERING INFORMATICS 53(2022):12.