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Identification of Surrounding Rock in TBM Excavation with Deep Neural Network
In this paper, based on the measured data of a water diversion project and combined with the existing research on the artificial neural network technology, a deep neural network model is trained to realize the real-time identification of surrounding rock in tunnel boring machine (TBM) excavation. The overall accuracy is above 85%. The result shows that deep learning technology can play a role in TBM geological prediction, and TBM operation can be guided by this method.
Identification of Surrounding Rock in TBM Excavation with Deep Neural Network
In this paper, based on the measured data of a water diversion project and combined with the existing research on the artificial neural network technology, a deep neural network model is trained to realize the real-time identification of surrounding rock in tunnel boring machine (TBM) excavation. The overall accuracy is above 85%. The result shows that deep learning technology can play a role in TBM geological prediction, and TBM operation can be guided by this method.
Identification of Surrounding Rock in TBM Excavation with Deep Neural Network
Nie, ShiWu (Autor:in) / Xue, Lin (Autor:in) / Jia, GuoPeng (Autor:in) / Ma, Yue (Autor:in) / Chen, Jing (Autor:in) / Huo, JunZhou (Autor:in)
01.05.2019
3377510 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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