Artificial neural networks in structural dynamics: A new modular radial basis function approach vs. convolutional and feedforward topologies

The aim of the present study is to develop a series of artificial neural networks (ANN) and to determine, by comparison to experiments, which type of neural network is able to predict the measured structural deformations most accurately. For this approach, three different ANNs are proposed. Firstly,...

Full description

Saved in:

Bibliographic Details
Published in:	Computer methods in applied mechanics and engineering Vol. 364; p. 112989
Main Authors:	Stoffel, Marcus, Gulakala, Rutwik, Bamer, Franz, Markert, Bernd
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01.06.2020 Elsevier BV
Subjects:	Artificial neural network Artificial neural networks Convolutional networks Modular structures Neural networks Numerical prediction Radial basis function Radial basis functions Shock tube experiments Structural mechanics Topology Radial basis functions 74K20 Structural mechanics 74-05 Artificial neural network Shock tube experiments Convolutional networks
ISSN:	0045-7825, 1879-2138
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!