ReP USP - Resultado da busca

Parte de monografia/livro
Application of cluster analysis to electricity generation data from the Santo Antônio Hydroelectric plant in the State of Rondônia, Brazil (2023)
Ribeiro, João Gabriel; Dias, Carlos Tadeu dos Santos ; Piedade, Sônia Maria de Stefano ; Vale, Giovane Maia do; Oliveira, Vlademir de Jesus Silva
Source: BTSym 2022, SIST. Emerging Trends and Challenges in Technology. Conference titles: Proceedings of the Brazilian Technology Symposium - BTSym’2. Unidade: ESALQ
Subjects: ANÁLISE DE CONGLOMERADOS, ELETRICIDADE, GERAÇÃO DE ENERGIA ELÉTRICA, USINAS HIDRELÉTRICAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIBEIRO, João Gabriel et al. Application of cluster analysis to electricity generation data from the Santo Antônio Hydroelectric plant in the State of Rondônia, Brazil. BTSym 2022, SIST. Emerging Trends and Challenges in Technology. Tradução . Cham: Springer Nature Switzerland AG, 2023. . Disponível em: https://doi.org/10.1007/978-3-031-31007-2_6. Acesso em: 12 jun. 2024.
APA
Ribeiro, J. G., Dias, C. T. dos S., Piedade, S. M. de S., Vale, G. M. do, & Oliveira, V. de J. S. (2023). Application of cluster analysis to electricity generation data from the Santo Antônio Hydroelectric plant in the State of Rondônia, Brazil. In BTSym 2022, SIST. Emerging Trends and Challenges in Technology. Cham: Springer Nature Switzerland AG. doi:10.1007/978-3-031-31007-2_6
NLM
Ribeiro JG, Dias CT dos S, Piedade SM de S, Vale GM do, Oliveira V de JS. Application of cluster analysis to electricity generation data from the Santo Antônio Hydroelectric plant in the State of Rondônia, Brazil [Internet]. In: BTSym 2022, SIST. Emerging Trends and Challenges in Technology. Cham: Springer Nature Switzerland AG; 2023. [citado 2024 jun. 12 ] Available from: https://doi.org/10.1007/978-3-031-31007-2_6
Vancouver
Ribeiro JG, Dias CT dos S, Piedade SM de S, Vale GM do, Oliveira V de JS. Application of cluster analysis to electricity generation data from the Santo Antônio Hydroelectric plant in the State of Rondônia, Brazil [Internet]. In: BTSym 2022, SIST. Emerging Trends and Challenges in Technology. Cham: Springer Nature Switzerland AG; 2023. [citado 2024 jun. 12 ] Available from: https://doi.org/10.1007/978-3-031-31007-2_6
Artigo de periodico
Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018 (2023)
Ribeiro, João Gabriel; Piedade, Sônia Maria de Stefano
Source: China Agricultural Economic Review. Unidade: ESALQ
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, EXPORTAÇÃO, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIBEIRO, João Gabriel e PIEDADE, Sônia Maria de Stefano. Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018. China Agricultural Economic Review, v. 15, n. 1, p. 46-65, 2023Tradução . . Disponível em: https://doi.org/10.1108/CAER-01-2022-0014. Acesso em: 12 jun. 2024.
APA
Ribeiro, J. G., & Piedade, S. M. de S. (2023). Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018. China Agricultural Economic Review, 15( 1), 46-65. doi:10.1108/CAER-01-2022-0014
NLM
Ribeiro JG, Piedade SM de S. Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018 [Internet]. China Agricultural Economic Review. 2023 ; 15( 1): 46-65.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1108/CAER-01-2022-0014
Vancouver
Ribeiro JG, Piedade SM de S. Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018 [Internet]. China Agricultural Economic Review. 2023 ; 15( 1): 46-65.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1108/CAER-01-2022-0014
Artigo de periodico
Applications of AMMI Bayesian Models in soybean production variables in the state of Mato Grosso, Brazil, from 1990 to 2020 (2023)
Ribeiro, João Gabriel ; Piedade, Sonia Maria de Stefano
Source: International Journal of Plant Production. Unidade: ESALQ
Subjects: DELINEAMENTO EXPERIMENTAL, INFERÊNCIA BAYESIANA, MODELOS MATEMÁTICOS, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIBEIRO, João Gabriel e PIEDADE, Sonia Maria de Stefano. Applications of AMMI Bayesian Models in soybean production variables in the state of Mato Grosso, Brazil, from 1990 to 2020. International Journal of Plant Production, v. 17, p. 365–378, 2023Tradução . . Disponível em: https://doi.org/10.1007/s42106-023-00245-4. Acesso em: 12 jun. 2024.
APA
Ribeiro, J. G., & Piedade, S. M. de S. (2023). Applications of AMMI Bayesian Models in soybean production variables in the state of Mato Grosso, Brazil, from 1990 to 2020. International Journal of Plant Production, 17, 365–378. doi:10.1007/s42106-023-00245-4
NLM
Ribeiro JG, Piedade SM de S. Applications of AMMI Bayesian Models in soybean production variables in the state of Mato Grosso, Brazil, from 1990 to 2020 [Internet]. International Journal of Plant Production. 2023 ; 17 365–378.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1007/s42106-023-00245-4
Vancouver
Ribeiro JG, Piedade SM de S. Applications of AMMI Bayesian Models in soybean production variables in the state of Mato Grosso, Brazil, from 1990 to 2020 [Internet]. International Journal of Plant Production. 2023 ; 17 365–378.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1007/s42106-023-00245-4
Tese (Doutorado)
Analysis of soybean crop data in the state of Mato Grosso, Brazil, in the period from 1990 to 2018 (2021)
Ribeiro, João Gabriel; Piedade, Sonia Maria de Stefano (Orientador)
Unidade: ESALQ
Subjects: ANÁLISE DE DADOS, SAFRA, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIBEIRO, João Gabriel. Analysis of soybean crop data in the state of Mato Grosso, Brazil, in the period from 1990 to 2018. 2021. Tese (Doutorado) – Universidade de São Paulo, Piracicaba, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/11/11134/tde-10112021-114539/. Acesso em: 12 jun. 2024.
APA
Ribeiro, J. G. (2021). Analysis of soybean crop data in the state of Mato Grosso, Brazil, in the period from 1990 to 2018 (Tese (Doutorado). Universidade de São Paulo, Piracicaba. Recuperado de https://www.teses.usp.br/teses/disponiveis/11/11134/tde-10112021-114539/
NLM
Ribeiro JG. Analysis of soybean crop data in the state of Mato Grosso, Brazil, in the period from 1990 to 2018 [Internet]. 2021 ;[citado 2024 jun. 12 ] Available from: https://www.teses.usp.br/teses/disponiveis/11/11134/tde-10112021-114539/
Vancouver
Ribeiro JG. Analysis of soybean crop data in the state of Mato Grosso, Brazil, in the period from 1990 to 2018 [Internet]. 2021 ;[citado 2024 jun. 12 ] Available from: https://www.teses.usp.br/teses/disponiveis/11/11134/tde-10112021-114539/
Artigo de periodico
A regression model for extreme events and the presence of bimodality with application to energy generation data (2021)
Vasconcelos, Julio Cezar Souza ; Cordeiro, Gauss Moutinho; Ortega, Edwin Moises Marcos ; Ribeiro, João Gabriel
Source: IET Renewable Power Generation. Unidade: ESALQ
Subjects: DISTRIBUIÇÃO LOGÍSTICA, DISTRIBUIÇÃO LOGNORMAL, GERAÇÃO DE ENERGIA ELÉTRICA, MODELOS MATEMÁTICOS, REGRESSÃO LOGÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VASCONCELOS, Julio Cezar Souza et al. A regression model for extreme events and the presence of bimodality with application to energy generation data. IET Renewable Power Generation, v. 15, p. 452–461, 2021Tradução . . Disponível em: https://doi.org/10.1049/rpg2.12043. Acesso em: 12 jun. 2024.
APA
Vasconcelos, J. C. S., Cordeiro, G. M., Ortega, E. M. M., & Ribeiro, J. G. (2021). A regression model for extreme events and the presence of bimodality with application to energy generation data. IET Renewable Power Generation, 15, 452–461. doi:10.1049/rpg2.12043
NLM
Vasconcelos JCS, Cordeiro GM, Ortega EMM, Ribeiro JG. A regression model for extreme events and the presence of bimodality with application to energy generation data [Internet]. IET Renewable Power Generation. 2021 ; 15 452–461.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1049/rpg2.12043
Vancouver
Vasconcelos JCS, Cordeiro GM, Ortega EMM, Ribeiro JG. A regression model for extreme events and the presence of bimodality with application to energy generation data [Internet]. IET Renewable Power Generation. 2021 ; 15 452–461.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1049/rpg2.12043

USP Schools

ReP

Filtros

Authors

Subjects

Funding Agencies