Cargando…
Data-assisted reduced-order modeling of extreme events in complex dynamical systems
The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions...
Autores principales: | Wan, Zhong Yi, Vlachas, Pantelis, Koumoutsakos, Petros, Sapsis, Themistoklis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5967742/ https://www.ncbi.nlm.nih.gov/pubmed/29795631 http://dx.doi.org/10.1371/journal.pone.0197704 |
Ejemplares similares
-
Machine Learning Predictors of Extreme Events Occurring in Complex Dynamical Systems
por: Guth, Stephen, et al.
Publicado: (2019) -
A variational approach to probing extreme events in turbulent dynamical systems
por: Farazmand, Mohammad, et al.
Publicado: (2017) -
Sequential sampling strategy for extreme event statistics in nonlinear dynamical systems
por: Mohamad, Mustafa A., et al.
Publicado: (2018) -
Data driven inference for the repulsive exponent of the Lennard-Jones potential in molecular dynamics simulations
por: Kulakova, Lina, et al.
Publicado: (2017) -
Controlling extreme events on complex networks
por: Chen, Yu-Zhong, et al.
Publicado: (2014)