Mello, Danilo César de 
; Veloso, Gustavo Vieira ; Lana, Marcos Guedes de; Mello, Fellipe Alcantara de Oliveira ; Poppiel, Raul Roberto ; Cabrero, Diego Ribeiro Oquendo; Di Raimo, Luis Augusto Di Loreto ; Schaefer, Carlos Ernesto Gonçalves Reynaud; Fernandes Filho, Elpídio Inácio ; Leite, Emilson Pereira; Demattê, José Alexandre Melo
Fonte: Geoscientific Model Development. Unidade: ESALQ
Assuntos: ALGORITMOS, APRENDIZADO COMPUTACIONAL, FRAMEWORKS, GEOFÍSICA, MODELAGEM DE DADOS, SENSOR, SOLOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MELLO, Danilo César de et al. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes. Geoscientific Model Development, v. 15, p. 1219–1246, 2022Tradução . . Disponível em: https://doi.org/10.5194/gmd-15-1219-2022. Acesso em: 30 nov. 2025.APA
Mello, D. C. de, Veloso, G. V., Lana, M. G. de, Mello, F. A. de O., Poppiel, R. R., Cabrero, D. R. O., et al. (2022). A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes. Geoscientific Model Development, 15, 1219–1246. doi:10.5194/gmd-15-1219-2022NLM
Mello DC de, Veloso GV, Lana MG de, Mello FA de O, Poppiel RR, Cabrero DRO, Di Raimo LADL, Schaefer CEGR, Fernandes Filho EI, Leite EP, Demattê JAM. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes [Internet]. Geoscientific Model Development. 2022 ; 15 1219–1246.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-15-1219-2022Vancouver
Mello DC de, Veloso GV, Lana MG de, Mello FA de O, Poppiel RR, Cabrero DRO, Di Raimo LADL, Schaefer CEGR, Fernandes Filho EI, Leite EP, Demattê JAM. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes [Internet]. Geoscientific Model Development. 2022 ; 15 1219–1246.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-15-1219-2022
