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,...

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Veröffentlicht in:	Computer methods in applied mechanics and engineering Jg. 364; S. 112989
Hauptverfasser:	Stoffel, Marcus, Gulakala, Rutwik, Bamer, Franz, Markert, Bernd
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.06.2020 Elsevier BV
Schlagworte:	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-Zugang:	Volltext
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