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DOI | 10.1029/2020GL092133 |
A toy model to investigate stability of AI‐based dynamical systems | |
B. Balogh; D. Saint‐; Martin; A. Ribes | |
2021-04-06 | |
发表期刊 | Geophysical Research Letters
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出版年 | 2021 |
英文摘要 | The development of atmospheric parameterizations based on neural networks is often hampered by numerical instability issues. Previous attempts to replicate these issues in a toy model have proven ineffective. We introduce a new toy model for atmospheric dynamics, which consists in an extension of the Lorenz’63 model to a higher dimension. While feedforward neural networks trained on a single orbit can easily reproduce the dynamics of the Lorenz’63 model, they fail to reproduce the dynamics of the new toy model, leading to unstable trajectories. Instabilities become more frequent as the dimension of the new model increases, but are found to occur even in very low dimension. Training the feedforward neural network on a different learning sample, based on Latin Hypercube Sampling, solves the instability issue. Our results suggest that the design of the learning sample can significantly influence the stability of dynamical systems driven by neural networks. |
领域 | 气候变化 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/322056 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | B. Balogh,D. Saint‐,Martin,等. A toy model to investigate stability of AI‐based dynamical systems[J]. Geophysical Research Letters,2021. |
APA | B. Balogh,D. Saint‐,Martin,&A. Ribes.(2021).A toy model to investigate stability of AI‐based dynamical systems.Geophysical Research Letters. |
MLA | B. Balogh,et al."A toy model to investigate stability of AI‐based dynamical systems".Geophysical Research Letters (2021). |
条目包含的文件 | 条目无相关文件。 |
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