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Filtros : "Computers and Electronics in Agriculture" "COLHEDORAS" Limpar

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  • Artigo de periodico

    A Rolling Horizon scheme for rescheduling in agricultural harvest (2023)

    Santos, Fernando Montenegro dos; Pérez Galarce, Francisco; Monardes Concha, Carlos; Candia Vejar, Alfredo; Nagano, Marcelo Seido ; Gómez Lagos, Javier

    Source: Computers and Electronics in Agriculture. Unidade: EESC

    Subjects: COLHEITA, COLHEDORAS, ENGENHARIA DE PRODUÇÃO

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      SANTOS, Fernando Montenegro dos et al. A Rolling Horizon scheme for rescheduling in agricultural harvest. Computers and Electronics in Agriculture, v. 215, p. 1-15, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2023.108392. Acesso em: 15 nov. 2025.

    • APA

      Santos, F. M. dos, Pérez Galarce, F., Monardes Concha, C., Candia Vejar, A., Nagano, M. S., & Gómez Lagos, J. (2023). A Rolling Horizon scheme for rescheduling in agricultural harvest. Computers and Electronics in Agriculture, 215, 1-15. doi:10.1016/j.compag.2023.108392

    • NLM

      Santos FM dos, Pérez Galarce F, Monardes Concha C, Candia Vejar A, Nagano MS, Gómez Lagos J. A Rolling Horizon scheme for rescheduling in agricultural harvest [Internet]. Computers and Electronics in Agriculture. 2023 ; 215 1-15.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1016/j.compag.2023.108392

    • Vancouver

      Santos FM dos, Pérez Galarce F, Monardes Concha C, Candia Vejar A, Nagano MS, Gómez Lagos J. A Rolling Horizon scheme for rescheduling in agricultural harvest [Internet]. Computers and Electronics in Agriculture. 2023 ; 215 1-15.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1016/j.compag.2023.108392

  • Artigo de periodico

    Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches (2021)

    Maldaner, Leonardo Felipe ; Corrêdo, Lucas de Paula ; Canata, Tatiana Fernanda ; Molin, José Paulo

    Source: Computers and Electronics in Agriculture. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, COMPUTACIONAL, CANA-DE-AÇÚCAR, COLHEDORAS

    Acesso à fonteAcesso à fonteDOIHow to cite
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    • ABNT

      MALDANER, Leonardo Felipe et al. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches. Computers and Electronics in Agriculture, v. 181, p. 1-9, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2020.105945. Acesso em: 15 nov. 2025.

    • APA

      Maldaner, L. F., Corrêdo, L. de P., Canata, T. F., & Molin, J. P. (2021). Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches. Computers and Electronics in Agriculture, 181, 1-9. doi:10.1016/j.compag.2020.105945

    • NLM

      Maldaner LF, Corrêdo L de P, Canata TF, Molin JP. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches [Internet]. Computers and Electronics in Agriculture. 2021 ; 181 1-9.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1016/j.compag.2020.105945

    • Vancouver

      Maldaner LF, Corrêdo L de P, Canata TF, Molin JP. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches [Internet]. Computers and Electronics in Agriculture. 2021 ; 181 1-9.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1016/j.compag.2020.105945
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