A trend graph attention network for traffic prediction-Reference-Cited by-同舟云学术

A trend graph attention network for traffic prediction

Published:2023-04 Issue: Volume:623 Page:275-292
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Wang Chu,Tian Ran,Hu Jia,Ma Zhongyu

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference43 articles.

1. Introduction to Urban Computing;Zheng;Geomatics Inf. Sci. Wuhan Univ.,2015

2. Urban Computing: concepts, methodologies, and applications;Zheng;ACM Trans. Intell. Syst. Technol.,2014

3. C. Zheng, X. Fan, C. Wang, J. Qi, Gman: A graph multi-attention network for traffic prediction, in: Proceedings of the AAAI, 2020, pp. 1234–1241.

4. Integrating granger causality and vector auto-regression for traffic prediction of large-scale wlans;Lu;KSII Trans. Internet Inf. Syst.,2016

5. A tutorial on support vector regression;Smola;Stat. Comput.,2004

Cited by 18 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. Multi-scale synchronous contextual network for fine-grained urban flow inference;Information Sciences;2025-01

2. Separable contextual graph neural networks to identify tailgating-oriented traffic congestion;Expert Systems with Applications;2024-11

3. Multimodal joint prediction of traffic spatial-temporal data with graph sparse attention mechanism and bidirectional temporal convolutional network;Advanced Engineering Informatics;2024-10

4. A multi-scale spatiotemporal network traffic prediction method based on spiking neural model;Journal of Membrane Computing;2024-08-17

5. Generalized spatial–temporal regression graph convolutional transformer for traffic forecasting;Complex & Intelligent Systems;2024-08-10