Fonte: Brazilian Journal of Analytical Chemistry. Unidade: ICMC
Assuntos: BIOCOMBUSTÍVEIS, ALGORITMOS, APRENDIZADO COMPUTACIONAL
ABNT
LUNA, Aderval Severino et al. Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data. Brazilian Journal of Analytical Chemistry, v. 10, n. 39, p. 52-69, 2023Tradução . . Disponível em: https://doi.org/10.30744/brjac.2179-3425.AR-30-2022. Acesso em: 16 set. 2024.APA
Luna, A. S., Torres, A. R., Cunha, C. L., Lima, I. C. A. de, & Nonato, L. G. (2023). Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data. Brazilian Journal of Analytical Chemistry, 10( 39), 52-69. doi:10.30744/brjac.2179-3425.AR-30-2022NLM
Luna AS, Torres AR, Cunha CL, Lima ICA de, Nonato LG. Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data [Internet]. Brazilian Journal of Analytical Chemistry. 2023 ; 10( 39): 52-69.[citado 2024 set. 16 ] Available from: https://doi.org/10.30744/brjac.2179-3425.AR-30-2022Vancouver
Luna AS, Torres AR, Cunha CL, Lima ICA de, Nonato LG. Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data [Internet]. Brazilian Journal of Analytical Chemistry. 2023 ; 10( 39): 52-69.[citado 2024 set. 16 ] Available from: https://doi.org/10.30744/brjac.2179-3425.AR-30-2022