State-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering
Significant uncertainties can be found in the modelling of geotechnical materials. This can
be attributed to the complex behaviour of soils and rocks amidst construction processes …
be attributed to the complex behaviour of soils and rocks amidst construction processes …
[HTML][HTML] Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models
A comparison between deep learning and standalone models in predicting the compaction
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
A comparative study of different machine learning algorithms in predicting EPB shield behaviour: a case study at the Xi'an metro, China
XD Bai, WC Cheng, G Li - Acta geotechnica, 2021 - Springer
Complex geological conditions and/or inappropriate shield tunnel boring machine (TBM)
operation can significantly degrade both the excavation and safety of tunnel construction. In …
operation can significantly degrade both the excavation and safety of tunnel construction. In …
Machine learning techniques to predict rock strength parameters
A Mahmoodzadeh, M Mohammadi… - Rock Mechanics and …, 2022 - Springer
To accurately estimate the rock shear strength parameters of cohesion (C) and friction angle
(φ), triaxial tests must be carried out at different stress levels so that a failure envelope can …
(φ), triaxial tests must be carried out at different stress levels so that a failure envelope can …
Prediction of safety factors for slope stability: comparison of machine learning techniques
Because of the disasters associated with slope failure, the analysis and forecasting of slope
stability for geotechnical engineers are crucial. In this work, in order to forecast the factor of …
stability for geotechnical engineers are crucial. In this work, in order to forecast the factor of …
Presenting the best prediction model of water inflow into drill and blast tunnels among several machine learning techniques
During the construction of a tunnel, water inflow is one of the most common and complex
geological disasters and has a large impact on the construction schedule and safety. When …
geological disasters and has a large impact on the construction schedule and safety. When …
Machine Learning in the Stochastic Analysis of Slope Stability: A State-of-the-Art Review
In traditional slope stability analysis, it is assumed that some “average” or appropriately
“conservative” properties operate over the entire region of interest. This kind of deterministic …
“conservative” properties operate over the entire region of interest. This kind of deterministic …
Machine learning forecasting models of disc cutters life of tunnel boring machine
This study aims to propose four Machine Learning methods of Gaussian process regression
(GPR), support vector regression (SVR), decision trees (DT), and K-nearest neighbors …
(GPR), support vector regression (SVR), decision trees (DT), and K-nearest neighbors …
Shield machine position prediction and anomaly detection during tunnelling in loess region using ensemble and deep learning algorithms
Tunnelling in urban areas should be aware of deviations from the design tunnel axis,
referred to also as 'misalignment'. Significant misalignment can cause unfavourable soil …
referred to also as 'misalignment'. Significant misalignment can cause unfavourable soil …
Cooperative prediction method of gas emission from mining face based on feature selection and machine learning
J Zhou, H Lin, H Jin, S Li, Z Yan, S Huang - International Journal of Coal …, 2022 - Springer
Collaborative prediction model of gas emission quantity was built by feature selection and
supervised machine learning algorithm to improve the scientific and accurate prediction of …
supervised machine learning algorithm to improve the scientific and accurate prediction of …