Semi-supervised method for tunnel blasting quality prediction using measurement while drilling data

Predicting blasting quality during tunnel construction holds practical significance. In this study, a new semi-supervised learning method using convolutional variational autoencoder (CVAE) and deep neural network (DNN) is proposed for the prediction of blasting quality grades. Tunnel blasting qualit...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Journal of Rock Mechanics and Geotechnical Engineering Jg. 17; H. 5; S. 2633 - 2649
Hauptverfasser:	Jin, Hengxiang, Fang, Qian, Wang, Jun, Chen, Jiayao, Wang, Gan, Zheng, Guoli
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.05.2025 Elsevier
Schlagworte:	Measurement while drilling (MWD) Over/under excavation Semi-supervised learning Tunnel blasting quality Over/under excavation Measurement while drilling (MWD) Semi-supervised learning Tunnel blasting quality
ISSN:	1674-7755
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!