Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Neural network application in forecasting maximum wall deflection in homogenous clay
Highlights Neural Networks was used to forecast maximum deflection of braced excavation in homogeneous clay and its position. A sensitivity analysis was accomplished to examine the relative significance of the parameters that influence the models. The results confirm that the developed ANN model is able to predict maximum deflection and its position reliably. Design charts were developed based on the ANN model.
Neural network application in forecasting maximum wall deflection in homogenous clay
Highlights Neural Networks was used to forecast maximum deflection of braced excavation in homogeneous clay and its position. A sensitivity analysis was accomplished to examine the relative significance of the parameters that influence the models. The results confirm that the developed ANN model is able to predict maximum deflection and its position reliably. Design charts were developed based on the ANN model.
Neural network application in forecasting maximum wall deflection in homogenous clay
Khalid R. Aljanabi (Autor:in) / Osamah M. AL-Azzawi (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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Estimation of Wall Deflection in Deep Excavation-Neural Network Approach
| British Library Conference Proceedings | 2006
A method to estimate wall deflection of braced excavations in clay
| British Library Conference Proceedings | 1987
| British Library Online Contents | 2016