Application of artificial intelligence in distinguishing genuine microseismic events from the noise signals in underground mines
The discrimination of genuine microseismic events from the noise signals during microseismic monitoring in underground mines is critical to prevent misinterpretations and correctly detect the highly stressed zones prone to rockbursting. This study proposes a novel mathematical classifier using genet...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Published: |
Elsevier
2024
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/95283 |