更正：奥卢瓦桑米等人。用于交通预测的多头时空注意力图卷积网络。2023年，，3836。
Correction: Oluwasanmi et al. Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction. 2023, , 3836.
作者信息
Oluwasanmi Ariyo, Aftab Muhammad Umar, Qin Zhiguang, Sarfraz Muhammad Shahzad, Yu Yang, Rauf Hafiz Tayyab
机构信息
School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.
Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan.
出版信息
Sensors (Basel). 2024 Dec 23;24(24):8214. doi: 10.3390/s24248214.
Abstract
In the original publication [...].
摘要
在原始出版物中[...]。
相似文献
1
Correction: Oluwasanmi et al. Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction. 2023, , 3836.更正：奥卢瓦桑米等人。用于交通预测的多头时空注意力图卷积网络。2023年，，3836。
Sensors (Basel). 2024 Dec 23;24(24):8214. doi: 10.3390/s24248214.
2
Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction.多头时空注意力图卷积网络的交通预测。
Sensors (Basel). 2023 Apr 9;23(8):3836. doi: 10.3390/s23083836.
3
IGAGCN: Information geometry and attention-based spatiotemporal graph convolutional networks for traffic flow prediction.IGAGCN：用于交通流预测的基于信息几何和注意力的时空图卷积网络。
Neural Netw. 2021 Nov;143:355-367. doi: 10.1016/j.neunet.2021.05.035. Epub 2021 Jun 7.
4
SGGformer: Shifted Graph Convolutional Graph-Transformer for Traffic Prediction.SGGformer：用于交通预测的移位图卷积图变换器
Sensors (Basel). 2022 Nov 21;22(22):9024. doi: 10.3390/s22229024.
5
Graph convolution networks based on adaptive spatiotemporal attention for traffic flow forecasting.基于自适应时空注意力的图卷积网络用于交通流预测。
Sci Rep. 2025 Mar 15;15(1):8935. doi: 10.1038/s41598-025-88706-w.
6
GATR: A Road Network Traffic Violation Prediction Method Based on Graph Attention Network.基于图注意力网络的道路网络交通违规预测方法（GATR）
Int J Environ Res Public Health. 2023 Feb 15;20(4):3432. doi: 10.3390/ijerph20043432.
7
Cross-Attention Fusion Based Spatial-Temporal Multi-Graph Convolutional Network for Traffic Flow Prediction.基于交叉注意力融合的时空多图卷积网络用于交通流预测
Sensors (Basel). 2021 Dec 18;21(24):8468. doi: 10.3390/s21248468.
8
Temporal representation learning enhanced dynamic adversarial graph convolutional network for traffic flow prediction.用于交通流预测的时态表征学习增强动态对抗图卷积网络
Sci Rep. 2025 Mar 11;15(1):8330. doi: 10.1038/s41598-025-93168-1.
9
Linear attention based spatiotemporal multi graph GCN for traffic flow prediction.基于线性注意力的时空多图GCN用于交通流预测。
Sci Rep. 2025 Mar 10;15(1):8249. doi: 10.1038/s41598-025-93179-y.
10
Spatial-Temporal Attention Mechanism and Graph Convolutional Networks for Destination Prediction.用于目的地预测的时空注意力机制与图卷积网络
Front Neurorobot. 2022 Jul 6;16:925210. doi: 10.3389/fnbot.2022.925210. eCollection 2022.
本文引用的文献
1
Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction.多头时空注意力图卷积网络的交通预测。
Sensors (Basel). 2023 Apr 9;23(8):3836. doi: 10.3390/s23083836.
Zotero 插件