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Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective se...

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Bibliografske podrobnosti
izdano v:Proc Math Phys Eng Sci
Main Authors: Vlachas, Pantelis R., Byeon, Wonmin, Wan, Zhong Y., Sapsis, Themistoklis P., Koumoutsakos, Petros
Format: Artigo
Jezik:Inglês
Izdano: The Royal Society Publishing 2018
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC5990702/
https://ncbi.nlm.nih.gov/pubmed/29887750
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rspa.2017.0844
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