skip to main content
Idioma:
Refinado por: Base de dados/Biblioteca: BACON - Mir@bel - GLOBAL_LIBRESACCES remover Nome da Publicação: Proceedings Of The National Academy Of Sciences remover assunto: Statistics remover
Result Number Material Type Add to My Shelf Action Record Details and Options
1
High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability
High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability
Material Type:
Artigo 		Adicionar ao Meu Espaço

High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability

Majda, Andrew J ; Abramov, Rafail ; Gershgorin, Boris

Proceedings of the National Academy of Sciences - PNAS, 2010-01, Vol.107 (2), p.581-586 [Periódico revisado por pares]

United States: National Academy of Sciences

Texto completo disponível

Citações Citado por
2
Statistical Equilibrium Predictions of Jets and Spots on Jupiter
Statistical Equilibrium Predictions of Jets and Spots on Jupiter
Material Type:
Artigo 		Adicionar ao Meu Espaço

Statistical Equilibrium Predictions of Jets and Spots on Jupiter

Turkington, Bruce ; Majda, Andrew ; Haven, Kyle ; DiBattista, Mark

Proceedings of the National Academy of Sciences - PNAS, 2001-10, Vol.98 (22), p.12346-12350 [Periódico revisado por pares]

United States: National Academy of Sciences

Texto completo disponível

Citações Citado por
3
Statistically Relevant Conserved Quantities for Truncated Quasigeostrophic Flow
Statistically Relevant Conserved Quantities for Truncated Quasigeostrophic Flow
Material Type:
Artigo 		Adicionar ao Meu Espaço

Statistically Relevant Conserved Quantities for Truncated Quasigeostrophic Flow

Abramov, Rafail V. ; Majda, Andrew J.

Proceedings of the National Academy of Sciences - PNAS, 2003-04, Vol.100 (7), p.3841-3846 [Periódico revisado por pares]

United States: National Academy of Sciences

Texto completo disponível

Citações Citado por
4
Using machine learning to predict extreme events in complex systems
Using machine learning to predict extreme events in complex systems
Material Type:
Artigo 		Adicionar ao Meu Espaço

Using machine learning to predict extreme events in complex systems

Qi, Di ; Majda, Andrew J.

Proceedings of the National Academy of Sciences - PNAS, 2020-01, Vol.117 (1), p.52-59 [Periódico revisado por pares]

United States: National Academy of Sciences

Texto completo disponível

Citações Citado por

Personalize Seus Resultados

  1. Editar

Refine Search Results

Expandir Meus Resultados

  1.   

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

Buscando em bases de dados remotas. Favor aguardar.