A Novel Identification Approach Using RFECV–Optuna–XGBoost for Assessing Surrounding Rock Grade of Tunnel Boring Machine Based on Tunneling Parameters
In order to solve the problem of the poor adaptability of the TBM digging process to changes in geological conditions, a new TBM digging model is proposed. An ensemble learning prediction model based on XGBoost, combined with Optuna for hyperparameter optimization, enables the real-time identificati...
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| Principais autores: | , , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
MDPI AG
2024-03-01
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| Serija: | Applied Sciences |
| Teme: | |
| Online dostop: | https://www.mdpi.com/2076-3417/14/6/2347 |
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