Prediction of rock mass classification in tunnel boring machine tunneling using the principal component analysis (PCA)–gated recurrent unit (GRU) neural network
Abstract Due to the complexity of underground engineering geology, the tunnel boring machine (TBM) usually shows poor adaptability to the surrounding rock mass, leading to machine jamming and geological hazards. For the TBM project of Lanzhou Water Source Construction, this study proposed a neural n...
        Saved in:
      
    
          | Main Authors: | Ke Man, Liwen Wu, Xiaoli Liu, Zhifei Song, Kena Li, Nawnit Kumar | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | Wiley
    
        2024-12-01 | 
| Series: | Deep Underground Science and Engineering | 
| Subjects: | |
| Online Access: | https://doi.org/10.1002/dug2.12084 | 
| Tags: | Add Tag 
      No Tags, Be the first to tag this record!
   | 
Similar Items
- 
                
                    DIFFERENT ROLES AND DESIGNS OF HETERO-GATE DIELECTRIC IN SINGLE- AND DOUBLE-GATE TUNNEL FIELD-EFFECT TRANSISTORS        
                          
 by: Nguyễn Đăng Chiến, et al.
 Published: (2020-09-01)
- 
                
                    A New Approach to Designing Advance Stress Release Boreholes to Mitigate Rockburst Hazards in Deep Boring-Machine-Constructed Tunnels        
                          
 by: Zhenkun Xie, et al.
 Published: (2024-12-01)
- 
                
                    Boosting Model Interpretability for Transparent ML in TBM Tunneling        
                          
 by: Konstantinos N. Sioutas, et al.
 Published: (2024-12-01)
- 
                
                    Index Prediction Model Based on LASSO-PCA and Deep Learning        
                          
 by: Bo Xu, et al.
 Published: (2024-09-01)
- 
                
                    Evaluation of machine learning algorithms in tunnel boring machine applications: a case study in Mashhad metro line 3        
                          
 by: Morteza Abbasi, et al.
 Published: (2024-12-01)
 
       