Predicting temperatures in Brazilian states capitals via Machine Learning (2025)
- Authors:
- USP affiliated authors: CALDAS, IBERE LUIZ - IF ; MORAES, ANA LUIZA RODRIGUES DE - IF ; GABRICK, ENRIQUE CHIPICOSKI - IF
- Unidade: IF
- DOI: 10.1140/epjs/s11734-025-01710-z
- Subjects: MUDANÇA CLIMÁTICA; MINERAÇÃO DE DADOS; APRENDIZADO COMPUTACIONAL
- Keywords: CLIMATE CHANGE; COMPUTATIONAL INTELLIGENCE; DATA MINING; DROUGHT; MACHINE LEARNING; STATISTICAL LEARNING
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: Springer
- Publisher place: Heidelberg
- Date published: 2025
- Source:
- Título: European Physical Journal Special Topics
- Volume/Número/Paginação/Ano: Volume 234, pages 4663–4682, (2025)
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SILVA, Sidney T. da et al. Predicting temperatures in Brazilian states capitals via Machine Learning. European Physical Journal Special Topics, 2025Tradução . . Disponível em: https://doi.org/10.1140/epjs/s11734-025-01710-z. Acesso em: 27 jan. 2026. -
APA
Silva, S. T. da, Gabrick, E. C., Moraes, A. L. R. de, Viana, R. L., Batista, A. M., Caldas, I. L., & Kurths, J. (2025). Predicting temperatures in Brazilian states capitals via Machine Learning. European Physical Journal Special Topics. doi:10.1140/epjs/s11734-025-01710-z -
NLM
Silva ST da, Gabrick EC, Moraes ALR de, Viana RL, Batista AM, Caldas IL, Kurths J. Predicting temperatures in Brazilian states capitals via Machine Learning [Internet]. European Physical Journal Special Topics. 2025 ;[citado 2026 jan. 27 ] Available from: https://doi.org/10.1140/epjs/s11734-025-01710-z -
Vancouver
Silva ST da, Gabrick EC, Moraes ALR de, Viana RL, Batista AM, Caldas IL, Kurths J. Predicting temperatures in Brazilian states capitals via Machine Learning [Internet]. European Physical Journal Special Topics. 2025 ;[citado 2026 jan. 27 ] Available from: https://doi.org/10.1140/epjs/s11734-025-01710-z - Collapse of multi-headed chimera states in biologically based neuronal networks
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Informações sobre o DOI: 10.1140/epjs/s11734-025-01710-z (Fonte: oaDOI API)
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