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基于Bayes判别法强大的判别分类能力,将Bayes判别理论应用到深部硬岩岩爆预测当中.选取最大切向应力σθ、单轴抗压强度cσ、单轴抗拉强度tσ和弹性能量指数Wet作为影响岩爆的因素,建立了以σθ/cσ,cσ/tσ及Wet为判别因子的岩爆预测的Bayes判别模型,以国内外15个深部岩体实例为训练样本进行训练,利用训练好的模型对灵宝东峪矿区、平煤集团八矿深部开拓巷道和铜陵冬瓜山深埋硬岩矿山岩爆进行预测.实例研究表明:该模型回判估计误判率为0,预测结果与工程实例实际岩爆情况相符合.
Bayesian discriminant theory is applied to the prediction of deep hard rockburst.Based on the Bayes discriminant method, the Bayesian discriminant theory is applied to predict the rockburst in deep hard rock.The maximum tangential stress σθ, uniaxial compressive strength cσ, uniaxial tensile strength tσ and elastic energy index Wet are selected as Bayesian discriminant model of rockburst prediction with σθ / cσ, cσ / tσ and Wet as discriminant factors was established. Fifteen deep rock mass samples from domestic and abroad were used as training samples. Using the trained model The prediction of rockburst in Lingbao Dongyu mining area, Pingmei Group VIII deep mine hard rock roadway and Tongling Dongguashan deep hard rock mine is carried out.Example studies show that the false positive judgment rate of this model is 0, and the prediction results are in good agreement with engineering practice Rock burst consistent.