Fonte: Environmental Science: Atmospheres. Unidade: IAG
Assuntos: QUALIDADE DO AR, POLUIÇÃO ATMOSFÉRICA, APRENDIZADO COMPUTACIONAL
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: 13 nov. 2025.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/d3ea00126aNLM
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 2025 nov. 13 ] Available from: https://doi.org/10.1039/d3ea00126aVancouver
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 2025 nov. 13 ] Available from: https://doi.org/10.1039/d3ea00126a
