| Titre : |
Artificial neural networks for predicting the maximum surface settlement induced by EPB-TBM : the Algiers metro case |
| Type de document : |
document électronique |
| Auteurs : |
Ilies Ayari, Auteur ; Yacine Derbal, Auteur ; Sebaï, Souâd, Directeur de thèse |
| Editeur : |
[S.l.] : [s.n.] |
| Année de publication : |
2025 |
| Importance : |
1 fichier PDF (27.3 Mo) |
| Présentation : |
ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Génie Civil : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 92-94 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Artificial neural network
EPB-TBM Tunneling
Prediction of surface settlement
Machine learning |
| Index. décimale : |
PC00425 |
| Résumé : |
This thesis presents a methodology to correlate ground surface movements (settlement) with
tunnel boring machine (TBM) operation parameters , Tunnel geometry and Geotechnical pa-
rameters using an Artificial neural network model to predict maximum ground surface settle-
ment. Data analyzed were selected from the excavation of the extension of Algiers subway line
“1” (El-Harrach to H.B. Int. Airport) tunnel, which was performed by a shield TBM. The
surface settlements observed along the entire tunnel section of the project (Contract 1-9) were
satisfactorily reproduced by the proposed ANN model. A dedicated pre-processing procedure
was necessary to enhance the model’s predictive capability, followed by a sensitivity analysis
to assess the individual contribution of each feature. |
Artificial neural networks for predicting the maximum surface settlement induced by EPB-TBM : the Algiers metro case [document électronique] / Ilies Ayari, Auteur ; Yacine Derbal, Auteur ; Sebaï, Souâd, Directeur de thèse . - [S.l.] : [s.n.], 2025 . - 1 fichier PDF (27.3 Mo) : ill. Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Génie Civil : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 92-94 Langues : Anglais ( eng)
| Mots-clés : |
Artificial neural network
EPB-TBM Tunneling
Prediction of surface settlement
Machine learning |
| Index. décimale : |
PC00425 |
| Résumé : |
This thesis presents a methodology to correlate ground surface movements (settlement) with
tunnel boring machine (TBM) operation parameters , Tunnel geometry and Geotechnical pa-
rameters using an Artificial neural network model to predict maximum ground surface settle-
ment. Data analyzed were selected from the excavation of the extension of Algiers subway line
“1” (El-Harrach to H.B. Int. Airport) tunnel, which was performed by a shield TBM. The
surface settlements observed along the entire tunnel section of the project (Contract 1-9) were
satisfactorily reproduced by the proposed ANN model. A dedicated pre-processing procedure
was necessary to enhance the model’s predictive capability, followed by a sensitivity analysis
to assess the individual contribution of each feature. |
|
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