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...
Uložené v:
| Vydané v: | Computational mechanics Ročník 72; číslo 4; s. 765 - 786 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2023
Springer Nature B.V |
| Predmet: | |
| ISSN: | 0178-7675, 1432-0924 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
Buďte prvý, kto okomentuje tento záznam!