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DSGNN: A Dual-View Supergrid-Aware Graph Neural Network for Regional Air Quality Estimation
April 3, 2024, 4:41 a.m. | Xin Zhang, Ling Chen, Xing Tang, Hongyu Shi
cs.LG updates on arXiv.org arxiv.org
Abstract: Air quality estimation can provide air quality for target regions without air quality stations, which is useful for the public. Existing air quality estimation methods divide the study area into disjointed grid regions, and apply 2D convolution to model the spatial dependencies of adjacent grid regions based on the first law of geography, failing to model the spatial dependencies of distant grid regions. To this end, we propose a Dual-view Supergrid-aware Graph Neural Network (DSGNN) …
abstract air quality apply arxiv convolution cs.lg dependencies graph graph neural network grid network neural network public quality regional spatial study type view
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