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针对鲍店煤矿巷道围岩的特点,提出一种基于BP神经网络,可采用巷道围岩力学参数与巷道位移变形之间的非线性关系的围岩参数反分析方法,反演的围岩参数代入数值模型后与实测值比较,结果误差小、精度高。
Aiming at the characteristics of surrounding rock in BaoDian coal mine roadway, a back analysis method of surrounding rock parameters based on BP neural network can be used to analyze the nonlinear relationship between mechanical parameters of roadway surrounding rock and displacement of roadway. Compared with the measured value after the numerical model, the error of the result is small and the precision is high.