Spatial-Temporal Conv-Sequence Learning With Accident Encoding for Traffic Flow Prediction-Reference-Cited by-同舟云学术

Spatial-Temporal Conv-Sequence Learning With Accident Encoding for Traffic Flow Prediction

Published:2022-05-01 Issue:3 Volume:9 Page:1765-1775
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Liu Zichuan¹,Zhang Rui¹^ORCID,Wang Chen²^ORCID,Xiao Zhu³^ORCID,Jiang Hongbo³^ORCID

Affiliation:

1. Department of Computer Science and Technology, Wuhan University of Technology, Wuhan, China

2. Internet Technology and Engineering R&D Center (ITEC), School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

3. College of Computer Science and Electronic Engineering, Hunan University, Changsha, China

Funder

National Natural Science Foundation of China

Humanities and Social Sciences Foundation of Ministry of Education

Key R&D Project of Hunan Province of China

Hunan Provincial Water Resources Department

Hubei Key Laboratory of Transportation Internet of Things

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6488902/9781297/09721541.pdf?arnumber=9721541

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4. Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction

5. Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting

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