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应用统计学理论并结合工程实际,建立回采巷道锚杆支护效果分类的Fisher判别分析模型,选取围岩强度、巷道断面、采动影响系数、巷道埋深、围岩完整度、护巷煤柱宽度和支护强度等7个因素作为回采巷道锚杆支护效果分类判别因素。利用平顶山矿区18条深井动压回采巷道的相关数据作为学习样本进行学习,建立回采巷道锚杆支护效果的Fisher判别分析模型,求的相应线性判别函数。运用建立的模型对平顶山矿区的4条回采巷道锚杆支护效果进行分类预测,预测结果与实际情况吻合良好。
Based on the statistical theory and engineering practice, Fisher discriminant analysis model of bolt supporting effect of mining roadway is established. The surrounding rock strength, roadway profile, mining influence coefficient, roadway depth, surrounding rock integrity, Width and support strength of seven factors as the roadway bolt supporting effect classification discrimination factor. Using the data of 18 deep well dynamic pressure mining roadways in Pingdingshan Mining Area as learning samples, Fisher discriminant analysis model of bolt supporting effect in mining roadway is established and the corresponding linear discriminant function is obtained. The model is used to predict the bolt supporting effect of 4 mining roadways in Pingdingshan mining area. The prediction results are in good agreement with the actual conditions.