Research and Application of Rock Burst Hazard Assessment of the Working Face Based on the CF-TOPSIS Method

Abstract

Coal mining activities have intensified, and underground mining depths have increased, posing significant challenges for mitigating rock burst hazard. To address this issue, this paper proposes an improved comprehensive weighting prediction (CF-TOPSIS) method that predicts weight and grade indices for rock burst evaluation. The study introduces a novel variable coefficient method to optimize the conflict response problem and employs correlation forward and other techniques to minimize errors caused by large data differences. Based on these, the CRITIC objective weight algorithm model is established, and FAHP is used to optimize weighting factors to make the index weight of rock burst more reasonable, thus enhancing the accuracy of hazard assessment for working faces. Results from engineering examples show that the prediction results combined with field drill cutting methods and microseismic monitoring data verify the accuracy of the proposed method, indicating its feasibility and effectiveness in predicting rock burst hazard in underground coal mines.