Local dimension and finite time prediction in spatiotemporal chaotic systems
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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Data(s) |
27/05/2014
27/05/2014
01/06/2003
|
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. |
Identificador |
http://dx.doi.org/10.1103/PhysRevE.67.066204 Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 67, n. 6 2, 2003. 1063-651X http://hdl.handle.net/11449/67300 10.1103/PhysRevE.67.066204 WOS:000184085000038 2-s2.0-42749108043 2-s2.0-42749108043.pdf |
Idioma(s) |
eng |
Relação |
Physical Review E: Statistical, Nonlinear, and Soft Matter Physics |
Direitos |
openAccess |
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 |
Tipo |
info:eu-repo/semantics/article |