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Application of neural network to rock slope stability assessments

  • A. J. Li
  • , S. Y. Khoo
  • , Y. Wang
  • , A. V. Lyamin
  • Deakin University
  • University of Newcastle

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationNumerical Methods in Geotechnical Engineering - Proceedings of the 8th European Conference on Numerical Methods in Geotechnical Engineering, NUMGE 2014
PublisherTaylor and Francis - Balkema
Pages473-478
Number of pages6
ISBN (Print)9781138026872
StatePublished - 2014
Externally publishedYes
Event8th European Conference on Numerical Methods in Geotechnical Engineering, NUMGE 2014 - Delft, Netherlands
Duration: 18 Jun 201420 Jun 2014

Publication series

NameNumerical Methods in Geotechnical Engineering - Proceedings of the 8th European Conference on Numerical Methods in Geotechnical Engineering, NUMGE 2014
Volume1

Conference

Conference8th European Conference on Numerical Methods in Geotechnical Engineering, NUMGE 2014
Country/TerritoryNetherlands
CityDelft
Period18/06/1420/06/14

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