Application of artificial neural network in soil parameter identification for deep excavation numerical model
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2011, Vol 18, Issue 4
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.
Authors and Affiliations
Marek Wojciechowski
Keywords
Related Articles
- EP ID EP74040
- DOI -
- Views 145
- Downloads 0
Trefftz function for solving a quasi-static inverse problem of thermal stresses. (Received in the final form February 11, 2010)
The problem of thermal stresses in a hollow cylinder is considered. The problem is two-dimensional and the cross-section of the hollow cylinder is approximated as a long and thin rectangle as the ratio of the inner and o...
Analysis of the melting, burning and flame spread of polymers with the particle finite element method
A computational procedure for analysis of the melting, burning and flame spread of polymers under fire conditions is presented. The method, termed particle finite element method (PFEM), combines concepts from particle-ba...
Numerical simulation of single phase flow in a flotation machine
In the paper, the numerical model of the flow phenomena in the flotation machine is presented. The process of flotation consists of a number of phenomena which provide serious numerical difficulties. One can enumerate ro...
Problems of the equilibrium of a rigid body and mechanical systems. (Received in the final form August 12, 2009)
In this article one of the greatest generalized methods for establishing the equilibrium equations of a rigid body and the set of rigid bodies is proposed. It is related to six equations of moments of force about six the...
Bayesian neural networks and Gaussian processes in identification of concrete properties
This paper gives a concise overview of concrete properties prediction using advanced nonlinear regression approach and Bayesian inference. Feed-forward layered neural network (FLNN) with Markov chain Monte Carlo stochast...