Journal
2019 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND BIG DATA (ICAIBD 2019)
Volume -, Issue -, Pages 251-255Publisher
IEEE
DOI: 10.1109/icaibd.2019.8837034
Keywords
component; deep neural network; TBM; identification of surrounding rock
Funding
- National Natural Science Foundation of China [51875076]
- NSFC-Liaoning United Key fund [U1708255]
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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.
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