Cargando…

Spatiotemporal adaptive attention graph convolution network for city-level air quality prediction

Air pollution is a leading cause of human diseases. Accurate air quality predictions are critical to human health. However, it is difficult to extract spatiotemporal features among complex spatiotemporal dependencies effectively. Most existing methods focus on constructing multiple spatial dependenc...

Descripción completa

Detalles Bibliográficos
Autores principales:	Liu, Hexiang, Han, Qilong, Sun, Hui, Sheng, Jingyu, Yang, Ziyu
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432486/ https://www.ncbi.nlm.nih.gov/pubmed/37587186 http://dx.doi.org/10.1038/s41598-023-39286-0

Ejemplares similares

An Attention-Guided Spatiotemporal Graph Convolutional Network for Sleep Stage Classification
por: Li, Menglei, et al.
Publicado: (2022)

Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction
por: Oluwasanmi, Ariyo, et al.
Publicado: (2023)

Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model
por: Kim, Jungi, et al.
Publicado: (2022)

Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization
por: Zhang, Xitong, et al.
Publicado: (2022)

Attention-based message passing and dynamic graph convolution for spatiotemporal data imputation
por: Wang, Yifan, et al.
Publicado: (2023)

Adaptive Attention Memory Graph Convolutional Networks for Skeleton-Based Action Recognition
por: Liu, Di, et al.
Publicado: (2021)

Author Correction: Attention-based message passing and dynamic graph convolution for spatiotemporal data imputation
por: Wang, Yifan, et al.
Publicado: (2023)

Resting-State Functional MRI Adaptation with Attention Graph Convolution Network for Brain Disorder Identification
por: Chu, Ying, et al.
Publicado: (2022)

Graph convolutional networks with hierarchical multi-head attention for aspect-level sentiment classification
por: Li, Xiaowen, et al.
Publicado: (2022)

Identification of autism spectrum disorder based on functional near-infrared spectroscopy using adaptive spatiotemporal graph convolution network
por: Zhang, Haoran, et al.
Publicado: (2023)

Spatial-Temporal Attention Mechanism and Graph Convolutional Networks for Destination Prediction
por: Li, Cong, et al.
Publicado: (2022)

Road traffic flow prediction based on dynamic spatiotemporal graph attention network
por: Chen, Yuguang, et al.
Publicado: (2023)

Dynamic graph convolutional networks with attention mechanism for rumor detection on social media
por: Choi, Jiho, et al.
Publicado: (2021)

GCMM: graph convolution network based on multimodal attention mechanism for drug repurposing
por: Zhang, Fan, et al.
Publicado: (2022)

GCNSA: DNA storage encoding with a graph convolutional network and self-attention
por: Cao, Ben, et al.
Publicado: (2023)

Application of graph frequency attention convolutional neural networks in depression treatment response
por: Lu, Zihe, et al.
Publicado: (2023)

GraphQA: protein model quality assessment using graph convolutional networks
por: Baldassarre, Federico, et al.
Publicado: (2020)

Prediction of circRNA-Disease Associations Based on the Combination of Multi-Head Graph Attention Network and Graph Convolutional Network
por: Cao, Ruifen, et al.
Publicado: (2022)

MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction
por: Liu, Shaohua, et al.
Publicado: (2022)

Document-Level Biomedical Relation Extraction Using Graph Convolutional Network and Multihead Attention: Algorithm Development and Validation
por: Wang, Jian, et al.
Publicado: (2020)

STDP-based adaptive graph convolutional networks for automatic sleep staging
por: Zhao, Yuan, et al.
Publicado: (2023)

KAGN:knowledge-powered attention and graph convolutional networks for social media rumor detection
por: Cui, Wei, et al.
Publicado: (2023)

A heterogeneous graph convolutional attention network method for classification of autism spectrum disorder
por: Shao, Lizhen, et al.
Publicado: (2023)

Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia
por: Lei, Du, et al.
Publicado: (2022)

Using Graph Attention Network and Graph Convolutional Network to Explore Human CircRNA–Disease Associations Based on Multi-Source Data
por: Li, Guanghui, et al.
Publicado: (2022)

Adaptive Attention Convolutional Neural Network for Liver Tumor Segmentation
por: Luan, Shunyao, et al.
Publicado: (2021)

MiRNA-Drug Resistance Association Prediction Through the Attentive Multimodal Graph Convolutional Network
por: Niu, Yanqing, et al.
Publicado: (2022)

Multicomponent Spatial-Temporal Graph Attention Convolution Networks for Traffic Prediction with Spatially Sparse Data
por: Liu, Shaohua, et al.
Publicado: (2021)

Predicting miRNA-disease associations via layer attention graph convolutional network model
por: Han, Han, et al.
Publicado: (2022)

Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition
por: Al-Hammadi, Muneer, et al.
Publicado: (2022)

Multi-scale and attention enhanced graph convolution network for skeleton-based violence action recognition
por: Yang, Huaigang, et al.
Publicado: (2022)

Spatial–Temporal Self-Attention Enhanced Graph Convolutional Networks for Fitness Yoga Action Recognition
por: Wei, Guixiang, et al.
Publicado: (2023)

SGCN: A Graph Sparsifier Based on Graph Convolutional Networks
por: Li, Jiayu, et al.
Publicado: (2020)

Graph convolutional networks fusing motif-structure information
por: Wang, Bin, et al.
Publicado: (2022)

De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks
por: Marco Salas, Sergio, et al.
Publicado: (2022)

An Attention-Enhanced Multi-Scale and Dual Sign Language Recognition Network Based on a Graph Convolution Network
por: Meng, Lu, et al.
Publicado: (2021)

Attention enhanced capsule network for text classification by encoding syntactic dependency trees with graph convolutional neural network
por: Jia, Xudong, et al.
Publicado: (2022)

Whole and Part Adaptive Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition
por: Zuo, Qi, et al.
Publicado: (2020)

Cross-Attention Fusion Based Spatial-Temporal Multi-Graph Convolutional Network for Traffic Flow Prediction
por: Yu, Kun, et al.
Publicado: (2021)

Identifying SM-miRNA associations based on layer attention graph convolutional network and matrix decomposition
por: Ni, Jie, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_kesvju703dkh3tdoi18uelsh5v