Microseismic signal processing and rockburst disaster identification: A multi-task deep learning and machine learning approach
Underground engineering projects such as deep tunnel excavation often encounter rockburst disasters accompanied by numerous microseismic events. Rapid interpretation of microseismic signals is crucial for the timely identification of rockbursts. However, conventional processing encompasses multi-ste...
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| Principais autores: | , , , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Elsevier
2026-01-01
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| Serier: | Journal of Rock Mechanics and Geotechnical Engineering |
| Fag: | |
| Online adgang: | http://www.sciencedirect.com/science/article/pii/S1674775525004597 |
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