Meta-MSNet: Meta-Learning Based Multi-Source Data Fusion for Traffic Flow Prediction

doi:10.1109/LSP.2020.3037527

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 遥感图像处理团队

	Meta-MSNet: Meta-Learning Based Multi-Source Data Fusion for Traffic Flow Prediction
	Fang, Shen 1,3; Pan, Xianbing 2; Xiang, Shiming 1,3; Pan, Chunhong 3
刊名	IEEE SIGNAL PROCESSING LETTERS
	2021
卷号	28 页码:6-10
关键词	Data fusion deep learning graph convolution meta-learning traffic flow prediction traffic network
ISSN号	1070-9908
DOI	10.1109/LSP.2020.3037527
通讯作者	Xiang, Shiming(smxiang@nlpr.ia.ac.cn)
英文摘要	Traffic flow prediction is a challenging task while most existing works are faced with two main problems in extracting complicated intrinsic and extrinsic features. In terms of intrinsic features, current methods don't fully exploit different functions of short-term neighboring and long-term periodic temporal patterns. As for extrinsic features, recent works mainly employ hand-crafted fusion strategies to integrate external factors but remain generalization issues. To solve these problems, we propose a meta-learning based multi-source spatio-temporal network (Meta-MSNet). The Meta-MSNet is designed with an encoder-decoder structure. The encoder captures neighboring temporal dependencies while the decoder extracts periodic features. Furthermore, two meta-learning based fusion modules are designed to integrate multi-source external data both on temporal and spatial dimensions. Experiments on three real-world traffic datasets have verified the superiority of the proposed model.
资助项目	Major Project for New Generation of AI[2018AAA0100400] ; NationalNatural Science Foundation ofChina[91646207] ; NationalNatural Science Foundation ofChina[62076242] ; NationalNatural Science Foundation ofChina[61773377] ; NationalNatural Science Foundation ofChina[61976208]
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000608679700002
资助机构	Major Project for New Generation of AI ; NationalNatural Science Foundation ofChina
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42590]
专题	自动化研究所_模式识别国家重点实验室_遥感图像处理团队
通讯作者	Xiang, Shiming
作者单位	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China 2.Chongqing Univ Posts & Telecommun, Coll Mobile Telecommun, Chongqing 400065, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Fang, Shen,Pan, Xianbing,Xiang, Shiming,et al. Meta-MSNet: Meta-Learning Based Multi-Source Data Fusion for Traffic Flow Prediction[J]. IEEE SIGNAL PROCESSING LETTERS,2021,28:6-10.
APA	Fang, Shen,Pan, Xianbing,Xiang, Shiming,&Pan, Chunhong.(2021).Meta-MSNet: Meta-Learning Based Multi-Source Data Fusion for Traffic Flow Prediction.IEEE SIGNAL PROCESSING LETTERS,28,6-10.
MLA	Fang, Shen,et al."Meta-MSNet: Meta-Learning Based Multi-Source Data Fusion for Traffic Flow Prediction".IEEE SIGNAL PROCESSING LETTERS 28(2021):6-10.