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Explainable sequence-to-sequence GRU neural network for pollution forecasting
The goal of pollution forecasting models is to allow the prediction and control of the air quality. Non-linear data-driven approaches based on deep neural networks have been increasingly used in such contexts showing significant improvements w.r.t. more conventional approaches like regression models...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10279754/ https://www.ncbi.nlm.nih.gov/pubmed/37336995 http://dx.doi.org/10.1038/s41598-023-35963-2 |