Multi-objective methods for crop insurance premiums: framework proposal and a case study in sugarcane (2021)
- Authors:
- USP affiliated authors: MENDIONDO, EDUARDO MARIO - EESC ; SARAIVA, ANTONIO MAURO - EP ; MARQUES, PATRICIA ANGÉLICA ALVES - ESALQ ; DELBEM, ALEXANDRE CLÁUDIO BOTAZZO - ICMC ; SILVA, ROBERTO FRAY DA - IEA ; BENSO, MARCOS ROBERTO - EESC ; GESUALDO, GABRIELA CHIQUITO - EESC
- Unidades: EESC; EP; ESALQ; ICMC; IEA
- DOI: 10.1080/00029890.1986.11971867
- Subjects: AGRICULTURA; SEGURO AGRÍCOLA; OTIMIZAÇÃO MATEMÁTICA; ESTUDO DE CASO
- Keywords: Insurance premiums
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Porto Alegre
- Date published: 2021
- Source:
- Conference titles: Congresso Brasileiro de Agroinformática
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SILVA, Roberto Fray da et al. Multi-objective methods for crop insurance premiums: framework proposal and a case study in sugarcane. 2021, Anais.. Porto Alegre: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2021. Disponível em: https://doi.org/10.1080/00029890.1986.11971867. Acesso em: 02 out. 2024. -
APA
Silva, R. F. da, Benso, M. R., Gesualdo, G. C., Mendiondo, E. M., Saraiva, A. M., Marques, P. A. A., & Delbem, A. C. B. (2021). Multi-objective methods for crop insurance premiums: framework proposal and a case study in sugarcane. In Anais. Porto Alegre: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1080/00029890.1986.11971867 -
NLM
Silva RF da, Benso MR, Gesualdo GC, Mendiondo EM, Saraiva AM, Marques PAA, Delbem ACB. Multi-objective methods for crop insurance premiums: framework proposal and a case study in sugarcane [Internet]. Anais. 2021 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1080/00029890.1986.11971867 -
Vancouver
Silva RF da, Benso MR, Gesualdo GC, Mendiondo EM, Saraiva AM, Marques PAA, Delbem ACB. Multi-objective methods for crop insurance premiums: framework proposal and a case study in sugarcane [Internet]. Anais. 2021 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1080/00029890.1986.11971867 - A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning
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Informações sobre o DOI: 10.1080/00029890.1986.11971867 (Fonte: oaDOI API)
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