深凹露天矿山岩质高陡边坡稳定性预测

结合大冶铁矿东露天高陡边坡，运用线性和非线性方法研究了岩质高陡边坡的稳定性预测模型。首先采用岩质边坡稳定性分析复合指标对边坡岩体质量进行分级；在此基础上，分别运用多元线性回归和BP神经网络方法研究边坡稳定性预测模型，并将其结果与极限平衡分析方法进行对比。结果表明，边坡稳定性与其影响因素之间存在着复杂的非线性关系，应用BP神经网络方法预测露天矿山高陡岩质边坡稳定性是有效的、可行的。

Stability Forecast of High Steep Rocky Slope in Deep Open-Pit Mine

Stability forecast model for high steep rocky slope was studied by Linear and nonlinear methods with the case of east open-pit high steep slope in Daye Iron Mine. Firstly, slope rockmass was classified by the composite index of rocky slope stability analysis. Based on this, forecast model for slope stability was studied by multivariate linear regression and BP neural network methods,and the results were compared with those by limit equilibrium method. The comparison results indicate that there is complex nonlinear relationship between the slope stability and its influencing factors, and it is feasible and effective to use BP neural network to forecast the stability of high steep rocky slope in open-pit mines.