PM2.5 prediction and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration using spatial temporal graph convolutional networks
In the context of rapid urbanization, PM _2.5 pollution poses a significant threat to public health and environmental quality. Current spatiotemporal analysis methods often lack sufficient accuracy. To address this, this study uses spatiotemporal analysis and Spatial Temporal Graph Convolutional Net...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Environmental Research Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2515-7620/ade1aa |
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