- Spatiotemporal adaptive attention graph convolution network for city ...🔍
- Spatiotemporal attention aided graph convolution networks for ...🔍
- Spatial|Temporal Adaptive Graph Convolution Network with ...🔍
- Spatiotemporal Adaptive Attention Graph Convolution Network for ...🔍
- Spatiotemporal Adaptive Gated Graph Convolution Network for ...🔍
- Dynamic Graph Convolutional Network with Attention Fusion ...🔍
- Spatial|Temporal Convolutional Graph Attention Networks for ...🔍
- A Multi|Adaptive Graph Convolutional Network for Traffic Forecasting🔍
Spatiotemporal adaptive attention graph convolution network for city ...
Spatiotemporal adaptive attention graph convolution network for city ...
In this paper, we propose a novel deep learning model, the spatiotemporal adaptive attention graph convolution model, for city-level air quality prediction.
Spatiotemporal adaptive attention graph convolution network for city ...
Spatiotemporal adaptive attention graph convolution network for city-level air quality prediction. Sci Rep. 2023 Aug 16;13(1):13335. doi: 10.1038/s41598-023 ...
Spatiotemporal attention aided graph convolution networks for ...
We propose a spectrum prediction method based on an attention-aided graph convolutional neural network (AttGCN) to capture features in both spatial and ...
(PDF) Spatiotemporal adaptive attention graph convolution network ...
In this paper, we propose a novel deep learning model, the spatiotemporal adaptive attention graph convolution model, for city-level air quality prediction, in ...
Spatial-Temporal Adaptive Graph Convolution Network with ...
The paper introduces a novel STACGCN model for enhancing traffic speed prediction in urban traffic management and planning, addressing the limitations of ...
Spatiotemporal Adaptive Attention Graph Convolution Network for ...
In this paper, we propose a novel deep learning model, the spatiotemporal adaptive attention graph convolution model (STAA-GCN), for city-level air quality ...
Spatiotemporal Adaptive Attention Graph Convolution Network for ...
In the methods based on GCN, all monitoring stations of the whole city are regarded as nodes in the graph, and correlations correspond to the ...
Spatiotemporal Adaptive Gated Graph Convolution Network for ...
This paper exploits spatiotemporal correlation of urban traffic flow and construct a dynamic weighted graph by seeking both spatial neighbors and semantic ...
AdpSTGCN: Adaptive spatial–temporal graph convolutional network ...
We propose an adaptive spatial–temporal graph convolutional network for traffic forecasting. Our approach exploits a multi-head attention mechanism to ...
Spatiotemporal Adaptive Gated Graph Convolution Network for ...
In this paper, we exploit spatiotemporal correlation of urban traffic flow and construct a dynamic weighted graph by seeking both spatial neighbors and ...
Spatiotemporal adaptive attention graph convolution network for city ...
AbstractAir pollution is a leading cause of human diseases. Accurate air quality predictions are critical to human health. However, it is difficult to ...
Dynamic Graph Convolutional Network with Attention Fusion ... - arXiv
... graph convolution network with spatial-temporal attention fusion ... 'Spatiotemporal adaptive gated graph convolution network for urban.
Spatial-Temporal Convolutional Graph Attention Networks for ...
In this work, a new traffic prediction framework--Spatial-Temporal Convolutional Graph Attention Network (ST-CGA) is proposed, to enable the traffic ...
A Multi-Adaptive Graph Convolutional Network for Traffic Forecasting
... urban computing to intelligent transportation. Recently, graph convoluti. ... spatiotemporal graph, have attracted lots of attention. However, existing ...
SASTGCN: A Self-Adaptive Spatio-Temporal Graph Convolutional ...
Traffic prediction plays a significant part in creating intelligent cities such as traffic management, urban computing, and public safety.
Spatio‐temporal adaptive graph convolutional networks for traffic ...
[25] further added the spatial and temporal attention mechanisms based on MCSTGCN to extract spatio-temporal features separately, improving the ...
Traffic flow prediction based on graph wave adaptive spatiotemporal ...
... attention. In summary, we propose a new model: the Spatiotemporal Graph Convolutional Network based on Graph Wavelet Adaptation. This model ...
jwwthu/GNN4Traffic: This is the repository for the collection ... - GitHub
Graph Attention Convolutional Network: Spatiotemporal Modeling for Urban ... Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic ...
Gated Fusion Adaptive Graph Neural Network for Urban Road ...
... convolution with an attention network. GWNET-conv [43]: ... Adaptive spatial-temporal graph attention networks for traffic flow forecasting.
An adaptive adjacency matrix-based graph convolutional recurrent ...
Spatiotemporal adaptive attention graph convolution network for city-level air quality prediction. Article Open access 16 August 2023 ...