[HTML][HTML] State-of-the-art review of soft computing applications in underground excavations

W Zhang, R Zhang, C Wu, ATC Goh, S Lacasse… - Geoscience …, 2020 - Elsevier
Soft computing techniques are becoming even more popular and particularly amenable to
model the complex behaviors of most geotechnical engineering systems since they have …

[HTML][HTML] Rockburst in underground excavations: A review of mechanism, classification, and prediction methods

M Askaripour, A Saeidi, A Rouleau… - Underground …, 2022 - Elsevier
Technical challenges have always been part of underground mining activities, however,
some of these challenges grow in complexity as mining occurs in deeper and deeper …

Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration

Y Qiu, J Zhou, M Khandelwal, H Yang, P Yang… - Engineering with …, 2022 - Springer
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 …

Short-term rockburst damage assessment in burst-prone mines: An explainable XGBOOST hybrid model with SCSO algorithm

Y Qiu, J Zhou - Rock Mechanics and Rock Engineering, 2023 - Springer
Rockburst can cause significant damage to infrastructure and equipment, and pose a
substantial risk to the safety of mine workers. Effective prediction of short-term rockburst …

Short-term rockburst prediction in underground project: insights from an explainable and interpretable ensemble learning model

Y Qiu, J Zhou - Acta Geotechnica, 2023 - Springer
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 …

Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate

J Zhou, Y Qiu, S Zhu, DJ Armaghani, C Li… - … Applications of Artificial …, 2021 - Elsevier
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 …

A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model

J Duan, PG Asteris, H Nguyen, XN Bui… - Engineering with …, 2021 - Springer
Recycled aggregate concrete is used as an alternative material in construction engineering,
aiming to environmental protection and sustainable development. However, the …

[HTML][HTML] Predicting TBM penetration rate in hard rock condition: a comparative study among six XGB-based metaheuristic techniques

J Zhou, Y Qiu, DJ Armaghani, W Zhang, C Li, S Zhu… - Geoscience …, 2021 - Elsevier
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 …

Evaluation method of rockburst: state-of-the-art literature review

J Zhou, X Li, HS Mitri - Tunnelling and Underground Space Technology, 2018 - Elsevier
The evaluation of rockburst is becoming increasingly important as mining activities reach
greater depths below the ground surface. In the literature, rockburst assessment has been …

Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories

J Zhou, E Li, S Yang, M Wang, X Shi, S Yao, HS Mitri - Safety Science, 2019 - Elsevier
Prediction of slope stability is one of the most crucial tasks in mining and geotechnical
engineering projects. The accuracy of the prediction is very important for mitigating the risk …