Advanced air quality prediction using multimodal data and dynamic modeling techniques
Abstract Accurate air quality forecasting is critical for human health and sustainable atmospheric management. To address this challenge, we propose a novel hybrid deep learning model that combines cutting-edge techniques, including CNNs, BiLSTM, attention mechanisms, GNNs, and Neural ODEs, to enhan...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11039-1 |
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