Cargando…
Model Error, Information Barriers, State Estimation and Prediction in Complex Multiscale Systems
Complex multiscale systems are ubiquitous in many areas. This research expository article discusses the development and applications of a recent information-theoretic framework as well as novel reduced-order nonlinear modeling strategies for understanding and predicting complex multiscale systems. T...
Autores principales: | Majda, Andrew J., Chen, Nan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513168/ https://www.ncbi.nlm.nih.gov/pubmed/33265733 http://dx.doi.org/10.3390/e20090644 |
Ejemplares similares
-
Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification
por: Chen, Nan, et al.
Publicado: (2018) -
Information theory and stochastics for multiscale nonlinear systems
por: Majda, Andrew J, et al.
Publicado: (2005) -
Evolution, development and complexity: multiscale evolutionary models of complex adaptive systems
por: Georgiev, Georgi, et al.
Publicado: (2019) -
Beating the curse of dimension with accurate statistics for the Fokker–Planck equation in complex turbulent systems
por: Chen, Nan, et al.
Publicado: (2017) -
Using machine learning to predict extreme events in complex systems
por: Qi, Di, et al.
Publicado: (2020)