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Prediction of maximum surface settlement caused by earth pressure balance shield tunneling using random forest

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Application of soft computing techniques in tunnelling and underground excavations: state of the art and future prospects
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Reinforcement learning based optimizer for improvement of predicting tunneling-induced ground responses
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Real-time analysis and regulation of EPB shield steering using Random Forest
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Forecasting maximum surface settlement caused by urban tunneling
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Surface settlement prediction for urban tunneling using machine learning algorithms with Bayesian optimization
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Spatial-temporal fusion network for maximum ground surface settlement prediction during tunnel excavation
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Forecasting and early warning of shield tunnelling-induced ground collapse in rock-soil interface mixed ground using multivariate data fusion and Catastrophe Theory
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Support vector regression with heuristic optimization algorithms for predicting the ground surface displacement induced by EPB shield tunneling
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Comparison of machine learning methods for ground settlement prediction with different tunneling datasets
inferred← citeshttps://doi.org/10.1016/j.jrmge.2021.08.018openalex-snapshot
Effectiveness of predicting tunneling-induced ground settlements using machine learning methods with small datasets
inferred← citeshttps://doi.org/10.1016/j.jrmge.2022.01.002openalex-snapshot
Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method
inferred← citeshttps://doi.org/10.1016/j.jrmge.2022.03.005openalex-snapshot
Auto machine learning-based modelling and prediction of excavation-induced tunnel displacement
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Evaluation and prediction of earth pressure balance shield performance in complex rock strata: A case study in Dalian, China
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Significance of weather condition, human mobility, and vaccination on global COVID-19 transmission
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Dynamic prediction models of rock quality designation in tunneling projects
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Tunneling-induced settlement prediction using the hybrid feature selection method for feature optimization
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Developing two robust hybrid models for predicting tunnel deformation in squeezing prone grounds
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Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: A comparative study
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Diagnosing tunnel collapse sections based on TBM tunneling big data and deep learning: A case study on the Yinsong Project, China
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Prediction of tunnel deformation using PSO variant integrated with XGBoost and its TBM jamming application
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Multi-output prediction for TBM operation parameters based on stacking ensemble algorithm
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Intelligent prediction and visual optimization of surface settlement induced by earth pressure balance shield tunneling
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Use of soft computing techniques for tunneling optimization of tunnel boring machines
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Soft computing approach for prediction of surface settlement induced by earth pressure balance shield tunneling
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Feedback on a shared big dataset for intelligent TBM Part II: Application and forward look
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Surface Settlement Prediction of Rectangular Pipe-Jacking Tunnel Based on the Machine-Learning Algorithm
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inferred← citeshttps://doi.org/10.1111/mice.13512openalex-snapshot
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inferred← citeshttps://doi.org/10.1155/2022/4174768openalex-snapshot
Prediction of Surface Settlement Induced by Large-Diameter Shield Tunneling Based on Machine-Learning Algorithms
inferred← citeshttps://doi.org/10.1201/9781003299127-126openalex-snapshot
Prediction of tunneling-induced surface settlement using a Bi-LSTM model with high generalization performance
inferred← citeshttps://doi.org/10.1631/jzus.a2300011openalex-snapshot
Prediction of maximum upward displacement of shield tunnel linings during construction using particle swarm optimization-random forest algorithm
inferred← citeshttps://doi.org/10.1680/jsmic.20.00011openalex-snapshot
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inferred← citeshttps://doi.org/10.21203/rs.3.rs-4771476/v1openalex-snapshot
Intelligent support system for ground settlement management during TBM tunneling by combining machine learning with statistical analysis
inferred← citeshttps://doi.org/10.3389/feart.2025.1544650openalex-snapshot
TBM shield mud cake prediction model based on machine learning
inferred← citeshttps://doi.org/10.3389/feart.2025.1692577openalex-snapshot
Intelligent recognition of surrounding rock grades based on TBM tunneling parameters
inferred← citeshttps://doi.org/10.3390/app13042574openalex-snapshot
Hybrid Random Forest-Based Models for Earth Pressure Balance Tunneling-Induced Ground Settlement Prediction
inferred← citeshttps://doi.org/10.3390/app13169459openalex-snapshot
Safety Evaluation of Crossing Tunnel Engineering: A Case Study
inferred← citeshttps://doi.org/10.3390/buildings15162935openalex-snapshot
Analysis of the Temporal and Spatial Evolution Behavior of Earth Pressure in the Shield Chamber and the Ground Settlement Behavior During Shield Tunneling in Water-Rich Sand Layers
inferred← citeshttps://doi.org/10.3390/rs16152742openalex-snapshot
Random Forest—Based Identification of Factors Influencing Ground Deformation Due to Mining Seismicity
inferred← citeshttps://doi.org/10.3390/s25051600openalex-snapshot
Machine Learning-Based Measurement and Prediction of Ground Settlement Induced by Shield Tunneling Undercrossing Existing Tunnels in Composite Strata
inferred← citeshttps://doi.org/10.3390/su151411074openalex-snapshot
Physics-Informed Ensemble Machine Learning Framework for Improved Prediction of Tunneling-Induced Short- and Long-Term Ground Settlement
inferred← citeshttps://doi.org/10.54254/2755-2721/20/20231087openalex-snapshot
Analysis of machine learning-based applications for intelligent construction of shield tunnels
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Bearing Capacity of Shallow Foundations on Cohesionless Soils: A Random Forest Based Approach
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