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Application of neural network to rock slope stability assessments

Li, AJ, Khoo, S, Lyamin, AV and Wang, Y (2014) Application of neural network to rock slope stability assessments In: Numerical Methods in Geotechnical Engineering. UNSPECIFIED. ISBN 978-1-138-00146-6

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Abstract

It is known that rock masses are inhomogeneous, discontinuous media composed of rock material and naturally occurring discontinuities such as joints, fractures and bedding planes. These features make any analysis very difficult using simple theoretical solutions. Generally speaking, back analysis technique can be used to capture some implicit parameters for geotechnical problems. In order to perform back analyses, the procedure of trial and error is generally required. However, it would be time-consuming. This study aims at applying a neural network to do the back analysis for rock slope failures. The neural network tool will be trained by using the solutions of finite element upper and lower bound limit analysis methods. Therefore, the uncertain parameter can be obtained, particularly for rock mass disturbance

Item Type: Book Section
Divisions : Surrey research (other units)
Authors :
NameEmailORCID
Li, AJ
Khoo, S
Lyamin, AV
Wang, Yying.wang@surrey.ac.uk
Date : 18 June 2014
DOI : 10.1201/b17017-85
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 13:52
Last Modified : 18 Mar 2020 10:31
URI: http://epubs.surrey.ac.uk/id/eprint/840640

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