Silva, Roberto Fray da 
; Gesualdo, Gabriela Chiquito ; Benso, Marcos Roberto ; Fava, Maria Clara ; Mendiondo, Eduardo Mario ; Saraiva, Antonio Mauro ; Delbem, Alexandre Cláudio Botazzo
Source: Proceedings. Conference titles: IEEE International Workshop on Metrology for Agriculture and Forestry - MetroAgriFor. Unidades: EESC, EP, ICMC, IEA
Subjects: CANA-DE-AÇÚCAR, ZONA AGRÍCOLA, SECA
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SILVA, Roberto Fray da et al. A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning. Proceedings, 2021Tradução . . Disponível em: https://doi.org/10.1109/MetroAgriFor52389.2021.9628570. Acesso em: 05 nov. 2024.APA
Silva, R. F. da, Gesualdo, G. C., Benso, M. R., Fava, M. C., Mendiondo, E. M., Saraiva, A. M., & Delbem, A. C. B. (2021). A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning. Proceedings. doi:10.1109/MetroAgriFor52389.2021.9628570NLM
Silva RF da, Gesualdo GC, Benso MR, Fava MC, Mendiondo EM, Saraiva AM, Delbem ACB. A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning [Internet]. Proceedings. 2021 ;[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/MetroAgriFor52389.2021.9628570Vancouver
Silva RF da, Gesualdo GC, Benso MR, Fava MC, Mendiondo EM, Saraiva AM, Delbem ACB. A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning [Internet]. Proceedings. 2021 ;[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/MetroAgriFor52389.2021.9628570
