Spatial-temporal graph neural network for traffic forecasting: An overview and open research issues-Reference-Cited by-同舟云学术

Spatial-temporal graph neural network for traffic forecasting: An overview and open research issues

Published:2021-06-21 Issue: Volume: Page:
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Bui Khac-Hoai Nam^ORCID,Cho Jiho,Yi Hongsuk

Funder

IITP

Korea Institute of Science and Technology Information

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-021-02587-w.pdf

Reference39 articles.

1. Atwood J, Towsley D (2016) Diffusion-convolutional neural networks. In: Proceedings of the 29th annual conference on neural information processing systems (NeurIPS), pp 1993– 2001

2. Bronstein MM, Bruna J, LeCun Y, Szlam A, Vandergheynst P (2017) Geometric deep learning: Going beyond euclidean data. IEEE Signal Process Mag 34(4):18–42. https://doi.org/10.1109/MSP.2017.2693418

3. Bui KHN, Yi H, Cho J (2021) Uvds: a new dataset for traffic forecasting with spatial-temporal correlation. In: Proceedings of the 13th asian conference on intelligent information and database system (ACIIDS). Springer, pp 66–77

4. Bui KN, Jung JE, Camacho D (2017) Game theoretic approach on real-time decision making for iot-based traffic light control. Concurr Comput Pract Exp 29(11):e4077. https://doi.org/10.1002/cpe.4077

5. Bui KN, Oh H, Yi H (2020) Traffic density classification using sound datasets: an empirical study on traffic flow at asymmetric roads. IEEE Access 8:125,671–125,679. https://doi.org/10.1109/ACCESS.2020.3007917

Cited by 94 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. KaTaGCN: Knowledge-Augmented and Time-Aware Graph Convolutional Network for efficient traffic forecasting;Information Fusion;2024-11

2. Multiscale graph based spatio-temporal graph convolutional network for energy consumption prediction of natural gas transmission process;Energy;2024-10

3. Enhancement of traffic forecasting through graph neural network-based information fusion techniques;Information Fusion;2024-10

4. PM2ECGCN: Parallelized spatial-temporal structures of multi-lead ECG with graph convolution network for multi-center cardiac disease diagnosis;Expert Systems with Applications;2024-09

5. Vulnerability Detection via Multiple-Graph-Based Code Representation;IEEE Transactions on Software Engineering;2024-08