Non-stationarity and internal correlations of the occurrence process of mining-induced seismic events [PDF]
, 2017 core +1 more source
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.
europepmc +1 more source
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.
europepmc +1 more source
Rockburst intensity grading prediction based on the LOF-ENN-KNN model. [PDF]
Sci RepGe H, Zhang J, Ma C, Hui K, Li Y, Wu Z.
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Prediction of Rockburst at Mufulira Mine, Copperbelt, Zambia
Prediction of Rockburst at Mufulira Mine, Copperbelt, ZambiaThe overall aim of this study is to provide methods for prediction of rockburst in deep underground mines, using Mufulira mine in Zambia's Copperbelt as a case study. For over 40 years, Mufulira underground copper mine has been recording incidents of rockburst.
openaire
Rockburst grade evaluation and parameter sensitivity analysis based on SSA-PNN framework: Considering rock mass strength. [PDF]
PLoS OneZhou X, Jiang Y, Wang Z, Wang Y.
europepmc +1 more source
Prediction and classification technology of rockburst hazard in deep buried and high in-situ stress tunnel. [PDF]
Sci RepLi H, Yang Y, Zhang Z, Tang L.
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Comparative study of temperature effects on white sandstone and rockburst-like materials. [PDF]
PLoS One, 2022 Zhu Z +7 more
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Comparative study of unbalanced mining disaster risk level prediction based on artificial intelligence algorithms. [PDF]
Sci RepBin Z +7 more
europepmc +1 more source