Different artificial intelligence (AI) methods have been applied to various aspects of rock
mechanics, but the fact that none of these methods have been used as a standard implies …

Deep learning is a sub-field of artificial intelligence that combines feature engineering and
classification in one method. It is a data-driven technique that optimises a predictive model …

Blasting is the most popular method for rock fragmentation in open-pit mines. However, the
side effects caused by blasting operations include ground vibration, air overpressure (AOp) …

Due to the rapid industrialization and the development of the economy in each country, the
demand for energy is increasing rapidly. The coal mines have to pace up the mining …

This study utilizes the support vector regression (SVR) model to predict the tunnel crown
displacement (TCD) induced by the blasting excavation. 95 blasting operations considering …

In this study, a new technique for predicting roadways stability in tunneling and underground
space was proposed based on a combination of particle swarm optimization (PSO) …

One of the main concerns associated with deep underground constructions is the violent
expulsion of rock induced by unexpected release of strain energy from surrounding rock …

Nowadays, an infectious disease outbreak is considered one of the most destructive effects
in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an …

Due to the lack of living space and the increase in population, there has been a construction
boom in the underground space to improve the quality of human life. Tunnel engineering …

This paper proposes a deep neural network (DNN)-based method for predicting ore
production by truck-haulage systems in open-pit mines. The proposed method utilizes two …