基于混沌神经网络方法的边坡稳定性分析

Slope Stability Analysis based on the Chaotic Neural Network Method

非线性科学为边坡稳定性分析提供了全新理论。搜集整理了大量边坡稳定或破坏实例,应用混沌神经网络方法构建的混沌神经网络模型,对边坡稳定性进行评价预测。把该方法应用到某露天矿边坡稳定性分析,结果表明混沌神经网络预测结果与传统极限平衡计算结果一致。同时应用该方法进行了影响边坡稳定各因素的敏感性分析,结果表明,内摩擦角、黏聚力、边坡角、边坡高度、重度对边坡稳定的敏感性依次降低。

Nonlinear science provides a completely new theory for the slope stability analysis. The chaotic neural net- work model based on the chaotic neural network theory is applied to evaluate and forecast the slope stability by collecting lots of the slope stability or damage cases. The application of this method to the slope stability of a certain open-pit indicated that the forecast result by the chaotic neural network is the same as that by the traditional limit equilibrium calculations. The method is also used for the sensitive analysis of the influent factors of the slope stability. The results show the sensitivity for the slope stability is decreasing in turn from the internal friction angle, cohesive force, slope angle to slope height.