DMGSTCN: Dynamic Multigraph Spatio–Temporal Convolution Network for Traffic Forecasting-Reference-Cited by-同舟云学术

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DMGSTCN: Dynamic Multigraph Spatio–Temporal Convolution Network for Traffic Forecasting

Published:2024-06-15 Issue:12 Volume:11 Page:22208-22219
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Qin Yanjun¹^ORCID,Tao Xiaoming¹^ORCID,Fang Yuchen²^ORCID,Luo Haiyong³^ORCID,Zhao Fang²^ORCID,Wang Chenxing²^ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University, Beijing, China

2. School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing, China

3. Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Xplore Prize 2021 in Information and Electronics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10551641/10478107.pdf?arnumber=10478107

Reference62 articles.

1. Intelligent Transportation Systems

2. Knowledge-Driven Industrial Intelligent System: Concept, Reference Model, and Application Direction

3. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting;Li

4. Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results

5. Integrating Granger Causality and Vector Auto-Regression for Traffic Prediction of Large-Scale WLANs

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