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Application of neural network to rock slope stability assessments

Li, A.J., Khoo, S.Y., Wang, Y. and Lyamin, A.V. 2014, Application of neural network to rock slope stability assessments. In Hicks, Michael A., Brinkgreve, Ronald B.J. and Rohe, Alexander (ed), Numerical methods in geotechnical engineering, CRC Press, London, England, pp.473-478.

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Title Application of neural network to rock slope stability assessments
Author(s) Li, A.J.
Khoo, S.Y.
Wang, Y.
Lyamin, A.V.
Title of book Numerical methods in geotechnical engineering
Editor(s) Hicks, Michael A.
Brinkgreve, Ronald B.J.
Rohe, Alexander
Publication date 2014
Chapter number 79
Total chapters 117
Start page 473
End page 478
Total pages 6
Publisher CRC Press
Place of Publication London, England
Keyword(s) Science & Technology
Technology
Physical Sciences
Engineering, Geological
Geosciences, Multidisciplinary
Engineering
Geology
BROWN FAILURE CRITERION
STOCHASTIC NONLINEAR-SYSTEMS
CHARTS
Summary 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.
ISBN 9781138001466
Language eng
Field of Research 090501 Civil Geotechnical Engineering
Socio Economic Objective 870201 Civil Construction Design
HERDC Research category B1 Book chapter
ERA Research output type B Book chapter
Copyright notice ©2014, Taylor and Francis
Free to Read? Yes
Free to Read Start Date 2016-07-01
Persistent URL http://hdl.handle.net/10536/DRO/DU:30070564

Document type: Book Chapter
Collections: School of Engineering
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.