Enhancing spatial inference of air pollution using machine learning techniques with low-cost monitors in data-limited scenarios (2024)
- Authors:
- USP affiliated authors: ANDRADE, MARIA DE FATIMA - IAG ; KAMIGAUTI, LEONARDO YOSHIAKI - IAG
- Unidade: IAG
- DOI: 10.1039/d3ea00126a
- Subjects: QUALIDADE DO AR; POLUIÇÃO ATMOSFÉRICA; APRENDIZADO COMPUTACIONAL
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: United Kingdom
- Date published: 2024
- Source:
- Título: Environmental Science: Atmospheres
- ISSN: 2634-3606
- Volume/Número/Paginação/Ano: v. 4, n. 3, p. 342-350, March, 2024
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
KAMIGAUTI, Leonardo Yoshiaki et al. Enhancing spatial inference of air pollution using machine learning techniques with low-cost monitors in data-limited scenarios. Environmental Science: Atmospheres, v. 4, n. 3, p. 342-350, 2024Tradução . . Disponível em: https://doi.org/10.1039/d3ea00126a. Acesso em: 14 fev. 2026. -
APA
Kamigauti, L. Y., Perez, G. M. P., Martin, T. C. M., Andrade, M. de F., & Kumar, P. (2024). Enhancing spatial inference of air pollution using machine learning techniques with low-cost monitors in data-limited scenarios. Environmental Science: Atmospheres, 4( 3), 342-350. doi:10.1039/d3ea00126a -
NLM
Kamigauti LY, Perez GMP, Martin TCM, Andrade M de F, Kumar P. Enhancing spatial inference of air pollution using machine learning techniques with low-cost monitors in data-limited scenarios [Internet]. Environmental Science: Atmospheres. 2024 ; 4( 3): 342-350.[citado 2026 fev. 14 ] Available from: https://doi.org/10.1039/d3ea00126a -
Vancouver
Kamigauti LY, Perez GMP, Martin TCM, Andrade M de F, Kumar P. Enhancing spatial inference of air pollution using machine learning techniques with low-cost monitors in data-limited scenarios [Internet]. Environmental Science: Atmospheres. 2024 ; 4( 3): 342-350.[citado 2026 fev. 14 ] Available from: https://doi.org/10.1039/d3ea00126a - Veículos novos ainda emitem poluentes danosos à saúde, apesar da redução geral em São Paulo [Depoimento a Ivan Conterno]
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Informações sobre o DOI: 10.1039/d3ea00126a (Fonte: oaDOI API)
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