Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 26, issue 4
Articles | Volume 26, issue 4
https://doi.org/10.5194/npg-26-381-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-26-381-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 4
Research article
 | 
05 Nov 2019
Research article |  | 05 Nov 2019

Generalization properties of feed-forward neural networks trained on Lorenz systems

Sebastian Scher and Gabriele Messori

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Short summary
Neural networks are a technique that is widely used to predict the time evolution of physical systems. For this the past evolution of the system is shown to the neural network – it is trained – and then can be used to predict the evolution in the future. We show some limitations in this approach for certain systems that are important to consider when using neural networks for climate- and weather-related applications.
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