Experimental investigation on acoustic emission precursor of rockburst based on unsupervised machine learning method
The key to achieving rockburst warning lies in the understanding of rockburst precursors. Considering the correlation characteristics of rockburst acoustic emission (AE) parameters, a self-organizing map neural network (SOMNN) based method for rockburst precursor inversion was proposed. The feature...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2024-04-01
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| Series: | Rock Mechanics Bulletin |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773230423000720 |