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 …

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 …

Complex geological conditions and/or inappropriate shield tunnel boring machine (TBM)
operation can significantly degrade both the excavation and safety of tunnel construction. In …

The laboratory determination of maximum dry density (ρ dmax) and optimum moisture
content (w opt) of soils requires considerable time and energy. Efforts have been made in …

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 …

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 …

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 …

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 …

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 …

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 …