Recurrent and convolutional neural networks in structural dynamics: a modified attention steered encoder–decoder architecture versus LSTM versus GRU versus TCN topologies to predict the response of shock wave-loaded plates

The aim of the present study is to analyse and predict the structural deformations occurring during shock tube experiments with a series of recurrent and temporal convolutional neural networks. The goal is to determine the architecture that can best learn and predict physically and geometrically non...

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Bibliographic Details
Published in:Computational mechanics Vol. 72; no. 4; pp. 765 - 786
Main Authors: Tandale, Saurabh Balkrishna, Stoffel, Marcus
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2023
Springer Nature B.V
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ISSN:0178-7675, 1432-0924
Online Access:Get full text
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