Application of artificial neural network in soil parameter identification for deep excavation numerical model

  • Marek Wojciechowski Chair of Geotechnics and Engineering Structures, Technical University of Łódź

Abstract

In this paper, an artificial neural network (ANN) is used to approximate response of deep excavation numerical model on input parameters. The approximated model is then used in minimization procedure of the inverse problem, i.e. minimization of the differences between the response of the model (now, neural network) and the field measurements. ANN based objective function is continuous and differentiable thus gradient based optimization algorithm can be efficiently used in this problem. It is showed that initial approximation of the numerical model by means of ANN increase efficiency of the identification process without loss of accuracy.

Keywords

artificial neural network, parameter identification, deep excavation,

References

Published
Jan 25, 2017
How to Cite
WOJCIECHOWSKI, Marek. Application of artificial neural network in soil parameter identification for deep excavation numerical model. Computer Assisted Methods in Engineering and Science, [S.l.], v. 18, n. 4, p. 303–311, jan. 2017. ISSN 2956-5839. Available at: <https://cames.ippt.gov.pl/index.php/cames/article/view/109>. Date accessed: 21 nov. 2024.
Section
Articles