Articles | Volume 26, issue 4
https://doi.org/10.5194/npg-26-381-2019
https://doi.org/10.5194/npg-26-381-2019
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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Latest update: 27 Mar 2024
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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.