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Accurate identification of rock fracture types is crucial for the prediction and early warning of coal mine rockburst hazards. Microseismic monitoring has been widely used for detecting rock fractures. However. conventional machine learning methods for microseismic signal analysis exhibited limited feature extraction capabilities and were highly susceptible to noise. https://www.knowall.blog/

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