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http://acervodigital.unesp.br/handle/11449/67300- Título:
- Local dimension and finite time prediction in spatiotemporal chaotic systems
- Universidade Estadual Paulista (UNESP)
- Bharathidasan University
- 1063-651X
- 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.
- 1-Jun-2003
- Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 67, n. 6 2, 2003.
- 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
- http://dx.doi.org/10.1103/PhysRevE.67.066204
- Acesso aberto
- outro
- http://repositorio.unesp.br/handle/11449/67300
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