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

Authors

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

Keywords:

artificial neural network, parameter identification, deep excavation

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.

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Published

2017-01-25

Issue

pp. 303–311

Section

Articles

How to Cite

Wojciechowski, M. (2017). Application of artificial neural network in soil parameter identification for deep excavation numerical model. Computer Assisted Methods in Engineering and Science, 18(4), 303–311. https://cames3.ippt.pan.pl/index.php/cames/article/view/109