The promise of implementing machine learning in earthquake engineering: A state-of-the-art review

Y Xie, M Ebad Sichani, JE Padgett… - Earthquake …, 2020 - journals.sagepub.com
Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …

[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 …

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 …

Ensemble deep learning-based models to predict the resilient modulus of modified base materials subjected to wet-dry cycles

M Esmaeili-Falak, RS Benemaran - Geomechanics and …, 2023 - koreascience.kr
The resilient modulus (MR) of various pavement materials plays a significant role in the
pavement design by a mechanistic-empirical method. The MR determination is done by …

Optimization of random forest through the use of MVO, GWO and MFO in evaluating the stability of underground entry-type excavations

J Zhou, S Huang, Y Qiu - Tunnelling and Underground Space Technology, 2022 - Elsevier
The stability evaluation of underground entry-type excavations is a prerequisite of the entry-
type mining method, which directly affects whether workers can be provided with a safe and …

Predicting resilient modulus of flexible pavement foundation using extreme gradient boosting based optimised models

R Sarkhani Benemaran, M Esmaeili-Falak… - International Journal of …, 2023 - Taylor & Francis
Resilient modulus (MR) plays the most critical role in the evaluation and design of flexible
pavement foundations. MR is utilised as the principal parameter for representing stiffness …

[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 …

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 …

Employing a genetic algorithm and grey wolf optimizer for optimizing RF models to evaluate soil liquefaction potential

J Zhou, S Huang, T Zhou, DJ Armaghani… - Artificial intelligence …, 2022 - Springer
Among the research hotspots in geological/geotechnical engineering, research on the
prediction of soil liquefaction potential is still limited. In this research, several machine …