Multi-objective optimization for limiting tunnel-induced damages considering uncertainties
Due to the rapid development of the urban metro system, the situation of new excavation
work being conducted adjacent to existing tunnels is quite common and becomes prime …
work being conducted adjacent to existing tunnels is quite common and becomes prime …
Dynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm
H Chen, QG Shen, MJ Skibniewski, Y Cao, Y Liu - Information Fusion, 2025 - Elsevier
In this paper, a hybrid intelligent framework comprising Bayesian optimization (BO), gradient
boosting with categorical features (CatBoost) and the nondominated sorting genetic …
boosting with categorical features (CatBoost) and the nondominated sorting genetic …
Spatio-temporal feature fusion for real-time prediction of TBM operating parameters: A deep learning approach
X Fu, L Zhang - Automation in Construction, 2021 - Elsevier
This research provides a spatio-temporal approach to perform real-time forecasting for the
tunnel boring machine (TBM) operating parameters. By extracting the real-time TBM …
tunnel boring machine (TBM) operating parameters. By extracting the real-time TBM …
UnrollingNet: An attention-based deep learning approach for the segmentation of large-scale point clouds of tunnels
A novel projection-based learning method named UnrollingNet is developed to conduct a
multi-label segmentation of various objects including seepage from 3D point clouds of …
multi-label segmentation of various objects including seepage from 3D point clouds of …
Geological investigation and treatment measures against water inrush hazard in karst tunnels: A case study in Guiyang, southwest China
N Liu, J Pei, C Cao, X Liu, Y Huang, G Mei - Tunnelling and Underground …, 2022 - Elsevier
Unfavourable geological disasters, such as water inrush and gushing mud, are often
encountered during tunnel construction in karst areas. Whenever a large-scale water and …
encountered during tunnel construction in karst areas. Whenever a large-scale water and …
Enhanced prediction intervals of tunnel-induced settlement using the genetic algorithm and neural network
This paper constructs the prediction intervals (PIs) of the tunnels' settlement caused by the
shielding steering process. The hybrid genetic algorithm-neural network (GA-NN) is …
shielding steering process. The hybrid genetic algorithm-neural network (GA-NN) is …
Data-driven joint multi-objective prediction and optimization for advanced control during tunnel construction
This research develops a hybrid approach that integrates light gradient boosting machine
(LightGBM) and non-dominated sorting genetic algorithm II (NSGA-II) to optimize the tunnel …
(LightGBM) and non-dominated sorting genetic algorithm II (NSGA-II) to optimize the tunnel …
Probabilistic reliability assessment of twin tunnels considering fluid–solid coupling with physics-guided machine learning
Accurate predictions of the internal force of a tunnel lining (IFTL) and maximum ground
surface deformation (MGSD) are critical for avoiding unexpected accidents. This work …
surface deformation (MGSD) are critical for avoiding unexpected accidents. This work …
Three-dimensional face stability analysis of rock tunnels excavated in Hoek-Brown media with a novel multi-cone mechanism
In order to give a more accurate prediction of the required face pressure, this work revisits
the three-dimensional (3D) face stability problems of rock tunnels excavated in Hoek-Brown …
the three-dimensional (3D) face stability problems of rock tunnels excavated in Hoek-Brown …
Settlement-based framework for long-term serviceability assessment of immersed tunnels
C Tang, SY He, WH Zhou - Reliability Engineering & System Safety, 2022 - Elsevier
In immersed tunnels, the considerable settlement that can develop during their long-term
service period may induce structural damage that affects normal operations (ie …
service period may induce structural damage that affects normal operations (ie …