Corpus ID: 221112117

Machine Learning for Robust Identification of Complex Nonlinear Dynamical Systems: Applications to Earth Systems Modeling

@article{Yadav2020MachineLF,
  title={Machine Learning for Robust Identification of Complex Nonlinear Dynamical Systems: Applications to Earth Systems Modeling},
  author={Nishant Yadav and S. Chandu Ravela and Auroop Ratan Ganguly},
  journal={ArXiv},
  year={2020},
  volume={abs/2008.05590}
}
Systems exhibiting nonlinear dynamics, including but not limited to chaos, are ubiquitous across Earth Sciences such as Meteorology, Hydrology, Climate and Ecology, as well as Biology such as neural and cardiac processes. However, System Identification remains a challenge. In climate and earth systems models, while governing equations follow from first principles and understanding of key processes has steadily improved, the largest uncertainties are often caused by parameterizations such asโ€ฆย Expand
1 Citations
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