Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge
W Zhang, X Gu, L Tang, Y Yin, D Liu, Y Zhang - Gondwana Research, 2022 - Elsevier
Abstract The so-called Fourth Paradigm has witnessed a boom during the past two decades,
with large volumes of observational data becoming available to scientists and engineers …
with large volumes of observational data becoming available to scientists and engineers …
[HTML][HTML] State-of-the-art review of soft computing applications in underground excavations
Soft computing techniques are becoming even more popular and particularly amenable to
model the complex behaviors of most geotechnical engineering systems since they have …
model the complex behaviors of most geotechnical engineering systems since they have …
Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: A comparative study
Abstract Machine learning (ML) algorithms have been gradually used in predicting tunneling-
induced settlement, but there is no uniform process for establishing ML models and even …
induced settlement, but there is no uniform process for establishing ML models and even …
[HTML][HTML] Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods
In order to determine the appropriate model for predicting the maximum surface settlement
caused by EPB shield tunneling, three artificial neural network (ANN) methods, back …
caused by EPB shield tunneling, three artificial neural network (ANN) methods, back …
[HTML][HTML] Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method
Accurate prediction of shield tunneling-induced settlement is a complex problem that
requires consideration of many influential parameters. Recent studies reveal that machine …
requires consideration of many influential parameters. Recent studies reveal that machine …
A critical evaluation of machine learning and deep learning in shield-ground interaction prediction
The interaction between a shield machine and the ground is a complicated problem
involving numerous extrinsic and intrinsic factors. Machine learning (ML) algorithms have …
involving numerous extrinsic and intrinsic factors. Machine learning (ML) algorithms have …
Measurement and prediction of tunnelling-induced ground settlement in karst region by using expanding deep learning method
This paper presents the measurement and prediction of the tunnelling-induced surface
response in karst ground, Guangzhou, China. A predictive method of ground settlement is …
response in karst ground, Guangzhou, China. A predictive method of ground settlement is …
Forecasting maximum surface settlement caused by urban tunneling
In this article, maximum surface settlement (MSS) of urban tunnels was investigated on the
basis of three operational parameters of tunnel width, tunnel depth, excavation method, as …
basis of three operational parameters of tunnel width, tunnel depth, excavation method, as …
Safety prediction of shield tunnel construction using deep belief network and whale optimization algorithm
S Ge, W Gao, S Cui, X Chen, S Wang - Automation in Construction, 2022 - Elsevier
Due to ground loss and shallowly buried tunnels, there are serious safety problems in shield
tunnel construction. To comprehensively describe the safety of shield tunnel construction …
tunnel construction. To comprehensively describe the safety of shield tunnel construction …
[HTML][HTML] Effectiveness of predicting tunneling-induced ground settlements using machine learning methods with small datasets
Prediction of tunneling-induced ground settlements is an essential task, particularly for
tunneling in urban settings. Ground settlements should be limited within a tolerable …
tunneling in urban settings. Ground settlements should be limited within a tolerable …