Prediction of TBM tunneling parameters and rockburst grade based on CNN-LSTM model
Meitan kexue jishuIn order to improve the intelligent construction and disaster prediction capabilities of TBM in traffic water conservancy and deep coal mine engineering, the CNN-LSTM model combining the advantages of convolutional neural network (CNN) and long short ...
Ke MAN +4 more
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工程科学学报Rockburst disasters pose an increasing threat to the construction safety of deep-buried engineering; thus, rockburst prediction is crucial for ensuring construction safety.
Jiazhu LIU +5 more
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Classifying rockburst with confidence: A novel conformal prediction approach
International Journal of Mining Science and TechnologyThe scientific community recognizes the seriousness of rockbursts and the need for effective mitigation measures. The literature reports various successful applications of machine learning (ML) models for rockburst assessment; however, a significant question remains unanswered: How reliable are these models, and at what confidence level are ...
Bemah Ibrahim, Isaac Ahenkorah
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Research on rock burst prediction based on an integrated model
Scientific ReportsRockburst is a significant safety threat in coal mining, influenced by complex nonlinear dynamic characteristics and multi-factor coupling. This study proposes a rockburst risk prediction method based on the SSA-CNN-MoLSTM-Attention model.
Junming Zhang +7 more
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Early estimation method of rockburst and large deformation of surrounding rock based on the deep borehole test. [PDF]
Heliyon, 2023 Cui K, Yang Z.
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Prediction of rockburst classification using Support Vector Machine
IOP Conference Series: Earth and Environmental Science, 2021 Hengjiao Tian, Yadong Xue
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The risk assessment of rockburst intensity in the highway tunnel based on the variable fuzzy sets theory. [PDF]
Sci Rep, 2023 Wang AF, Yang XT, Gu XB.
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Measurement and Classification Criteria of Strength Decrease Rate and Brittleness Indicator Index for Rockburst Proneness Evaluation of Hard Rocks. [PDF]
Materials (Basel), 2023 Du K, Yang S, Zhou J, Wang L.
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Multi-Index Geophysical Monitoring and Early Warning for Rockburst in Coalmine: A Case Study. [PDF]
Int J Environ Res Public Health, 2022 Liu X +5 more
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Application of KNN-based isometric mapping and fuzzy c-means algorithm to predict short-term rockburst risk in deep underground projects. [PDF]
Front Public Health, 2022 Kamran M, Ullah B, Ahmad M, Sabri MMS.
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