Predicting microseismic, acoustic emission and electromagnetic radiation data using neural networks
Microseism, acoustic emission and electromagnetic radiation (M-A-E) data are usually used for predicting rockburst hazards. However, it is a great challenge to realize the prediction of M-A-E data. In this study, with the aid of a deep learning algorithm, a new method for the prediction of M-A-E dat...
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| Autors principals: | , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Elsevier
2024-02-01
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| Col·lecció: | Journal of Rock Mechanics and Geotechnical Engineering |
| Matèries: | |
| Accés en línia: | http://www.sciencedirect.com/science/article/pii/S1674775523001907 |
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