Publicação: Local dimension and finite time prediction in spatiotemporal chaotic systems
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Data
2003-06-01
Orientador
Coorientador
Pós-graduação
Curso de graduação
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Tipo
Artigo
Direito de acesso
Acesso aberto
Resumo
Predictability is related to the uncertainty in the outcome of future events during the evolution of the state of a system. The cluster weighted modeling (CWM) is interpreted as a tool to detect such an uncertainty and used it in spatially distributed systems. As such, the simple prediction algorithm in conjunction with the CWM forms a powerful set of methods to relate predictability and dimension.
Descrição
Palavras-chave
Algorithms, Boundary conditions, Eigenvalues and eigenfunctions, Forecasting, Matrix algebra, Probability, Probability distributions, Random processes, Statistical methods, Vectors, Bayesian modeling, Dynamical systems theory, Finite time prediction, Local dimension, Spatiotemporal chaotic system, Chaos theory
Idioma
Inglês
Como citar
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 67, n. 6 2, 2003.
