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| 2022, Vol. 59(4): 69-80 DOI: | ||
| Study on Prediction of TBM Tunnelling Parameters Based on Attentionenhanced Bi-LSTM Model | ||
| (1. School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083; 2. State Key Laboratory of Water and Sediment Science and Water Conservancy and Hydropower Engineering, Tsinghua University, Beijing 100084; 3. Huaneng Tibet Hydropower Safety Engineering Technology Research Center, Chengdu 610041) | ||
| Received null Revised null | ||
| Supporting info | ||
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