A prediction model on rockburst intensity grade based on variable weight and matter-element extension

Area of Science:

• Geotechnical Engineering
• Mining Engineering
• Disaster Prediction

Background:

• Rockbursts pose significant dynamic disaster risks in deep underground engineering projects.
• Accurate prediction of rockburst intensity is crucial for ensuring safety and operational integrity.
• Existing prediction models may lack sufficient accuracy or robustness.

Purpose of the Study:

• To develop and validate a novel rockburst prediction model integrating variable weight theory and matter-element extension theory.
• To enhance the accuracy and reliability of rockburst intensity grade prediction in underground engineering.
• To provide a new methodological approach for mitigating rockburst-related risks.

Main Methods:

• Variable weight theory was employed to optimize the weighting of key prediction indexes.
• Matter-element extension theory and the grade variable method were utilized to establish classification standards and intervals for rockburst intensity.
• The proposed model was tested on global engineering projects and compared against existing methods.

Main Results:

• The novel model demonstrated an improved correct prediction rate for rockburst intensity grades.
• The integration of variable weight theory and grade variable method enhanced the safety and reliability of the predictions.
• Comparative analysis confirmed the superior performance of the proposed model over other existing methods.

Conclusions:

• The developed rockburst prediction model offers a significant advancement in accurately assessing rockburst intensity.
• The combined application of variable weight theory and matter-element extension theory provides a robust framework for dynamic disaster prediction.
• This research presents a promising new approach for enhancing safety in deep underground engineering operations.