Publications by authors named "Xulong Yao"

Article Synopsis
  • * A composite prediction model is proposed that integrates various algorithms, including data balancing and unsupervised clustering, to enhance the accuracy and reliability of rock burst predictions.
  • * The study organizes and analyzes 301 rock burst data samples, using advanced techniques to optimize the data and improve sample balance, ultimately creating a more effective predictive model.
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The structure of rocks plays a crucial role in their failure process. However, it is ignored that the interactions between rock internal structure and the effect of its own evolution on the rock fracture process. To investigate the effect between the evolution law of rock regionalized structures and their interaction relationships during failure.

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The characteristics of acoustic emission signals generated in the process of rock deformation and fission contain rich information on internal rock damage. The use of acoustic emissions monitoring technology can analyze and identify the precursor information of rock failure. At present, in the field of acoustic emissions monitoring and the early warning of rock fracture disasters, there is no real-time identification method for a disaster precursor characteristic signal.

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