Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks
Sign Up to like & getrecommendations! Published in 2018 at "Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences"
DOI: 10.1098/rspa.2017.0844
Abstract: 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… read more here.
Keywords: high dimensional; dimensional chaotic; data driven; driven forecasting ... See more keywords
Data-Driven Forecasting of Postflutter Responses of Geometrically Nonlinear Wings
Sign Up to like & getrecommendations! Published in 2020 at "AIAA Journal"
DOI: 10.2514/1.j059024
Abstract: Ensuring adequate flutter margins is a critical step in aircraft design. However, in the presence of nonlinear effects, subcritical limit-cycle oscillations can arise even before flutter occurs. Wh... read more here.
Keywords: geometrically nonlinear; data driven; postflutter responses; driven forecasting ... See more keywords