Source: Computers and Electronics in Agriculture. Unidade: ESALQ
Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, CANA-DE-AÇÚCAR, IMAGEAMENTO DE SATÉLITE, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), SENSORIAMENTO REMOTO
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LUCIANO, Ana Cláudia dos Santos et al. Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm. Computers and Electronics in Agriculture, v. 18, p. 1-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2021.106063. Acesso em: 19 out. 2024.APA
Luciano, A. C. dos S., Picoli, M. C. A., Duft, D. G., Rocha, J. V., Leal, M. R. L. V., & Maire, G. le. (2021). Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm. Computers and Electronics in Agriculture, 18, 1-10. doi:10.1016/j.compag.2021.106063NLM
Luciano AC dos S, Picoli MCA, Duft DG, Rocha JV, Leal MRLV, Maire G le. Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm [Internet]. Computers and Electronics in Agriculture. 2021 ; 18 1-10.[citado 2024 out. 19 ] Available from: https://doi.org/10.1016/j.compag.2021.106063Vancouver
Luciano AC dos S, Picoli MCA, Duft DG, Rocha JV, Leal MRLV, Maire G le. Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm [Internet]. Computers and Electronics in Agriculture. 2021 ; 18 1-10.[citado 2024 out. 19 ] Available from: https://doi.org/10.1016/j.compag.2021.106063