LSTM-based approach for predicting periodic motions of an impacting system via transient dynamics

Dynamically impacting systems are characterised with inherent instability and complex non-linear phenomena which makes it practically difficult to predict the steady state response of the system at transient periods. This study investigates the ability of a data driven machine learning method using...

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Veröffentlicht in:	Neural networks 2021-08, Vol.140, p.49-64
Hauptverfasser:	Afebu, Kenneth Omokhagbo, Liu, Yang, Papatheou, Evangelos, Guo, Bingyong
Format:	Artikel
Sprache:	eng
Schlagworte:	Basin prediction Coexisting attractor Long Short-Term Memory network Percussive drilling Vibro-impact
Online-Zugang:	Volltext
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