Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
Systematic review of machine learning applications in mining: Exploration, exploitation, and reclamation
D Jung, Y Choi - Minerals, 2021 - mdpi.com
Recent developments in smart mining technology have enabled the production, collection,
and sharing of a large amount of data in real time. Therefore, research employing machine …
and sharing of a large amount of data in real time. Therefore, research employing machine …
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …
parameter for the successful accomplishment of a tunneling project, and the proper and …
[HTML][HTML] Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques
A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
[HTML][HTML] Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases
G Wang, B Zhao, B Wu, C Zhang, W Liu - International Journal of Mining …, 2023 - Elsevier
Slope stability prediction research is a complex non-linear system problem. In carrying out
slope stability prediction work, it often encounters low accuracy of prediction models and …
slope stability prediction work, it often encounters low accuracy of prediction models and …
Employing a genetic algorithm and grey wolf optimizer for optimizing RF models to evaluate soil liquefaction potential
Among the research hotspots in geological/geotechnical engineering, research on the
prediction of soil liquefaction potential is still limited. In this research, several machine …
prediction of soil liquefaction potential is still limited. In this research, several machine …
[HTML][HTML] Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization
The advance rate (AR) of a tunnel boring machine (TBM) under hard rock conditions is a key
parameter in the successful implementation of tunneling engineering. In this study, we …
parameter in the successful implementation of tunneling engineering. In this study, we …
Developing hybrid ELM-ALO, ELM-LSO and ELM-SOA models for predicting advance rate of TBM
Accurate prediction of TBM performance is very important for efficient completion of TBM
construction tunnel project. This paper aims to predict the advance rate (AR) of tunnel boring …
construction tunnel project. This paper aims to predict the advance rate (AR) of tunnel boring …
Slope stability classification under seismic conditions using several tree-based intelligent techniques
Slope stability analysis allows engineers to pinpoint risky areas, study trigger mechanisms
for slope failures, and design slopes with optimal safety and reliability. Before the …
for slope failures, and design slopes with optimal safety and reliability. Before the …
[HTML][HTML] Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms
Blasting is well-known as an effective method for fragmenting or moving rock in open-pit
mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical …
mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical …