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Prediction of Deep Excavation-induced Ground Surface Movements Using Artificial Neural Network  

유충식 (성균관대학교 토목환경공학과)
최병석 (성균관대학교 건축, 조경, 토목공학부 토목공학과)
Publication Information
Journal of the Korean Geotechnical Society / v.20, no.3, 2004 , pp. 53-65 More about this Journal
Abstract
This paper presents the prediction of deep excavation-induced ground surface movements using artificial neural network(ANN) technique, which is of prime importance in the damage assessment of adjacent buildings. A finite element model, which can realistically replicate deep excavation-induced ground movements, was employed to perform a parametric study on deep excavations with emphasis on ground movements. The result of the finite element analysis formed a basis for the Artificial Neural Network(ANN) system development. It was shown that the developed ANN system can be effective for a first-order prediction of ground movements associated with deep-excavation.
Keywords
Artificial neural network; Deep-excavation; Finite element analysis; Parametric study;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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