Predicting short-term rockburst intensity using a weighted probability stacking model with optimal feature selection and Bayesian hidden layer

J Sun, W Wang, L Xie - Tunnelling and Underground Space Technology, 2024 - Elsevier
Rockburst is the most common and severe geological hazard affecting the safe construction
of underground projects, which seriously endangers the security of construction personnel …

Predicting rockbursts in deep tunnels based on ejection velocity and kinetic energy measurements using advanced machine learning

A Mahmoodzadeh, N Ghazouani… - Automation in …, 2024 - Elsevier
Accurately predicting rockburst in deep tunnels is paramount, as it ensures the utmost safety,
minimizes costs and delays, and optimizes design and construction processes. In this paper …

A multi-criteria decision intelligence framework to predict fire danger ratings in underground engineering structures

M Kamran, W Chaudhry, RK Wattimena, H Rehman… - Fire, 2023 - mdpi.com
A wide variety of natural catastrophes are induced by coal mining, with fire hazard being one
of the most significant threats to underground engineering structures. In recent years, there …

Predicting short-term rockburst using rf–critic and improved cloud model

J Sun, W Wang, L Xie - Natural Resources Research, 2024 - Springer
Rockburst is a common ground pressure disaster in underground geotechnical engineering.
The frequent occurrence of rockburst hazards severely threatens the security of construction …

[HTML][HTML] Rockburst prediction using artificial intelligence techniques: A review

Y Zhang, K Fang, M He, D Liu, J Wang, Z Guo - Rock Mechanics Bulletin, 2024 - Elsevier
Rockburst is a phenomenon that occurs during mining when there is sudden, violent failure
of rock mass in deep underground areas or regions with high tectonic stress. Rockburst …

Efficient qualitative risk assessment of pipelines using relative risk score based on machine learning

CN Vanitha, SV Easwaramoorthy, SA Krishna, J Cho - Scientific reports, 2023 - nature.com
Pipelines are observed one of the economic modes of transport for transporting oil, gas, and
water between various locations. Most of the countries in the world transport petroleum and …

A deep learning-based combination method of spatio-temporal prediction for regional mining surface subsidence

Y Xiao, Q Tao, L Hu, R Liu, X Li - Scientific Reports, 2024 - nature.com
In coal mining areas, surface subsidence poses significant risks to human life and property.
Fortunately, surface subsidence caused by coal mining can be monitored and predicted by …

Neural networks based linear (PCA) and nonlinear (ISOMAP) feature extraction for soil swelling pressure prediction (North East Algeria)

B Ouassila, TF Zohra, L Laid, B Hizia - Heliyon, 2023 - cell.com
The swelling pressure (SP) of expansive soils is crucial for both geotechnical studies as well
as practitioners. Multiple attempts have been made to correlate the SP with the properties of …

A review of tunnel rockburst prediction methods based on static and dynamic indicators

Q Zhang, W Li, L Yuan, T Zheng, Z Liang, X Wang - Natural Hazards, 2024 - Springer
Rockbursts frequently occur in tunneling projects and pose a serious threat to workers and
the environment. Therefore, accurate prediction of rockbursts is of great practical …

[HTML][HTML] Experimental investigation on acoustic emission precursor of rockburst based on unsupervised machine learning method

J Sun, D Liu, P He, L Guo, B Cao, L Zhang, Z Li - Rock Mechanics Bulletin, 2024 - Elsevier
The key to achieving rockburst warning lies in the understanding of rockburst precursors.
Considering the correlation characteristics of rockburst acoustic emission (AE) parameters, a …