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 …
Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration
Accurate prediction of ground vibration caused by blasting has always been a significant
issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon …
issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon …
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 …
Developing a hybrid model of Jaya algorithm-based extreme gradient boosting machine to estimate blast-induced ground vibrations
Blasting is still being considered to be one the most important applicable alternatives for
conventional excavations. Ground vibration generated due to blasting is an undesirable …
conventional excavations. Ground vibration generated due to blasting is an undesirable …
[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 …
Short-term rockburst prediction in underground project: Insights from an explainable and interpretable ensemble learning model
Rockburst is a frequent challenge during tunnel and other underground construction and is
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …
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 …
Predicting tunnel squeezing using support vector machine optimized by whale optimization algorithm
The squeezing behavior of surrounding rock can be described as the time-dependent large
deformation during tunnel excavation, which appears in special geological conditions, such …
deformation during tunnel excavation, which appears in special geological conditions, such …
Prediction and analysis of train arrival delay based on XGBoost and Bayesian optimization
R Shi, X Xu, J Li, Y Li - Applied Soft Computing, 2021 - Elsevier
Accurate train arrival delay prediction is critical for real-time train dispatching and for the
improvement of the transportation service. This study proposes a data-driven method that …
improvement of the transportation service. This study proposes a data-driven method that …
Reduction of computational error by optimizing SVR kernel coefficients to simulate concrete compressive strength through the use of a human learning optimization …
This research presents a new model for finding optimal conditions in the concrete
technology area. To do that, results of a series of laboratory investigations on concrete …
technology area. To do that, results of a series of laboratory investigations on concrete …