LSTM-based approach for predicting periodic motions of an impacting system via transient dynamics-Reference-Cited by-同舟云学术

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

Published:2021-08 Issue: Volume:140 Page:49-64
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Afebu Kenneth Omokhagbo^ORCID,Liu Yang^ORCID,Papatheou Evangelos^ORCID,Guo Bingyong

Funder

PTDF

EPSRC

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference41 articles.

1. Afebu, K. O., Liu, Y., & Papatheou, E. (2019). LSTM-based approach for predicting periodic motions of an impacting system via transient dynamics. In The first international nonlinear dynamics conference. Rome, Italy.

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4. Invisible grazings and dangerous bifurcations in impacting systems: the problem of narrow-band chaos;Banerjee;Physical Review E,2009

5. A self-excited system for percussive-rotary drilling;Batako;Journal of Sound and Vibration,2003

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