基于D-S证据理论的岩爆预测方法研究.

To effectively predict rockburst, a rockburst prediction method based on D-S evidence theory is proposed. Firstly, six indicator factors related to rockburst occurrence are selected as evidence, and the basic probability assignment of evidence is constructed through fuzzy matter-element framework and normal type degree of membership function. Then, the evidence is classified using K-means and a combined fusion rule of fusing evidence within clusters in classical Dempster’s rule while fusing evidence between clusters in the weighted way is proposed to reduce the adverse effects of high conflict evidence fusion. Finally, the model is applied to the No. 2 shaft project of the Qinling Zhongnanshan highway tunnel and compared with the empirical method. To address the uncertainty in the prediction process and to estimate the probability of rockburst occurrence, Monte Carlo simulation is used to perform sampling simulations and the global sensitivity of the input indicators is measured by Spearman’s rank correlation coefficient. The results show that the influence of the input indicators varies widely and in different directions for different rockburst cases; the probability of occurrence of the five rockburst cases ranges from 40. 8% to 70. 1%. The model shows outstanding predictive classification performance and can provide reference for rockburst prediction in deeply buried underground projects. [ABSTRACT FROM AUTHOR]