[HTML][HTML] Rockburst in underground excavations: A review of mechanism, classification, and prediction methods
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 …
some of these challenges grow in complexity as mining occurs in deeper and deeper …
[HTML][HTML] Application of artificial intelligence to rock mechanics: An overview
AI Lawal, S Kwon - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
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 …
mechanics, but the fact that none of these methods have been used as a standard implies …
Strength of stacking technique of ensemble learning in rockburst prediction with imbalanced data: Comparison of eight single and ensemble models
Rockburst is a common dynamic geological hazard, severely restricting the development
and utilization of underground space and resources. As the depth of excavation and mining …
and utilization of underground space and resources. As the depth of excavation and mining …
Investigating photovoltaic solar power output forecasting using machine learning algorithms
Solar power integration in electrical grids is complicated due to dependence on volatile
weather conditions. To address this issue, continuous research and development is required …
weather conditions. To address this issue, continuous research and development is required …
[HTML][HTML] Machine learning methods for rockburst prediction-state-of-the-art review
One of the most serious mining disasters in underground mines is rockburst phenomena.
They can lead to injuries and even fatalities as well as damage to underground openings …
They can lead to injuries and even fatalities as well as damage to underground openings …
Real-time prediction of rockburst intensity using an integrated CNN-Adam-BO algorithm based on microseismic data and its engineering application
X Yin, Q Liu, X Huang, Y Pan - Tunnelling and Underground Space …, 2021 - Elsevier
Rockburst is a dynamic geological disaster common during underground excavation, which
significantly threatens the safety of personnel, equipment, and property. This paper …
significantly threatens the safety of personnel, equipment, and property. This paper …
[HTML][HTML] Intelligent rockburst prediction model with sample category balance using feedforward neural network and Bayesian optimization
The rockburst prediction becomes more and more challenging due to the development of
deep underground projects and constructions. Increasing numbers of intelligent algorithms …
deep underground projects and constructions. Increasing numbers of intelligent algorithms …
Predictive modeling of short-term rockburst for the stability of subsurface structures using machine learning approaches: T-SNE, K-Means clustering and XGBoost
Accurate prediction of short-term rockburst has a significant role in improving the safety of
workers in mining and geotechnical projects. The rockburst occurrence is nonlinearly …
workers in mining and geotechnical projects. The rockburst occurrence is nonlinearly …
Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments
Rockburst is a severe geological hazard that restricts deep mine operations and tunnel
constructions. To overcome the shortcomings of widely used algorithms in rockburst …
constructions. To overcome the shortcomings of widely used algorithms in rockburst …
[HTML][HTML] Use of machine learning algorithms to assess the state of rockburst hazard in underground coal mine openings
The risk of rockbursts is one of the main threats in hard coal mines. Compared to other
underground mines, the number of factors contributing to the rockburst at underground coal …
underground mines, the number of factors contributing to the rockburst at underground coal …