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http://dx.doi.org/10.12814/jkgss.2018.17.4.199

A Study on Development of Artificial Neural Network (ANN) for Deep Excavation Design  

Yoo, Chungsik (School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus)
Yang, Jaewon (School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus)
Abbas, Qaisar (School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus)
Aizaz, Haider Syed (School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus)
Publication Information
Journal of the Korean Geosynthetics Society / v.17, no.4, 2018 , pp. 199-212 More about this Journal
Abstract
This research concerns the prediction method for ground movement and wall member force due to determination structural stability check and failure check during deep excavation construction. First, research related with excavation influence parameters is conducted. Then, numerical analysis for various excavation conditions were conducted using Finite Element Method and Beam-column elasto-plasticity method. Excavation analysis database was then constructed. Using this database, development of ANN (artificial neural network) was performed for each ground movements and using structural member forces. By comparing the numerical analysis results with ANN's prediction, it is validated that development of ANN can be used efficient for prediction of ground movement and structural member forces in deep excavation site.
Keywords
Artificial neural network; Deep excavation; Ground movement; Finite element method; Elasto-plasticity method;
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Times Cited By KSCI : 1  (Citation Analysis)
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