Estimation of wall deflection in braced excavation in clays using artificial neural networks

Evan C.L. Hsiao, Gordon T.C. Kung, C. Hsein Juang, Matt Schuster

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

1 Scopus citations

Abstract

To investigate the serviceability reliability of a braced excavation system, a means has to be established for estimating wall deflection in the braced excavation. Traditionally, the wall deflection and ground settlement are "predicted" using finite element method (FEM) and/or other simplified methods. In this study, artificial neural networks (ANNs) are developed as an alternative of estimating the maximum wall deflection. The developed ANNs are validated with the collected 8 case histories of deep excavation that were not used in the development of these ANNs. Copyright ASCE 2006.

Original languageEnglish
Title of host publicationGeoCongress 2006
Subtitle of host publicationGeotechnical Engineering in the Information Technology Age
Pages128
Number of pages1
DOIs
StatePublished - 2006
EventGeoCongress 2006 - Atlanta, GA, United States
Duration: 26 Feb 20061 Mar 2006

Publication series

NameGeoCongress 2006: Geotechnical Engineering in the Information Technology Age
Volume2006

Conference

ConferenceGeoCongress 2006
Country/TerritoryUnited States
CityAtlanta, GA
Period26/02/061/03/06

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