Deep learning approach-based prediction of transfer functions in structure-acoustic coupling models

This study proposes a novel deep learning framework including an autoencoder and a convolutional neural network to predict transfer functions in the structure-acoustic-coupled model. The primary objective is to reduce the computational expenses typically associated with finite element method (FEM) s...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Linqi Yu, Yongqiang Qu, Bon-Heon Ku, Meng Zhang, Chin-Suk Hong, Jung Sub Lee, Mustafa Z. Yousif, Hee-Chang Lim
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	Elsevier 2025-12-01
Σειρά:	Results in Engineering
Θέματα:	Deep learning Convolutional neural networks Autoencoder Transfer functions Structure-acoustic coupling
Διαθέσιμο Online:	http://www.sciencedirect.com/science/article/pii/S2590123025041040
Ετικέτες:	Προσθήκη ετικέτας Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!