Heterogeneous Modular Traffic Prediction Based on Multilayer Graph Convolutional Network-Reference-Cited by-同舟云学术

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Heterogeneous Modular Traffic Prediction Based on Multilayer Graph Convolutional Network

Published:2024-07 Issue:7 Volume:25 Page:7805-7817
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Chang Mengmeng¹^ORCID,Ding Zhiming²^ORCID,Zhao Zilin³^ORCID,Cai Zhi⁴^ORCID

Affiliation:

1. College of Computer and Information Engineering, Henan Normal University, Xinxiang, China

2. Institute of Software, Chinese Academy of Sciences, Beijing, China

3. Faculty of Information Technology, Beijing University of Technology, Beijing, China

4. College of Computer Science, Beijing University of Technology, Beijing, China

Funder

National Natural Science of Foundation of China

National Key Research Development Program of China

Key Technology Research and Development Program of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10582787/10423889.pdf?arnumber=10423889

Reference48 articles.

1. A spatio-temporal sequence-to-sequence network for traffic flow prediction

2. Traffic congestion propagation inference using dynamic Bayesian graph convolution network

3. Random walks on hypergraphs

4. Grade: Graph dynamic embedding;Spasov;arXiv:2007.08060,2020

5. Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Temporal Hierarchical Graph Attention Network for Traffic Prediction with Prompt Learning;2024 International Wireless Communications and Mobile Computing (IWCMC);2024-05-27

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