边坡稳定性神经网络评价模型中断裂构造的定量化处理

神经网络模型应用于边坡稳定性评价已取得不少成果，但总体上仍处于理论研究阶段，因子的选择及因子的定量化处理问题尚无统一认识，因断裂构造因素难以量化处理，很多评价中未进行考虑，影响了边坡稳定性评价的效果。本文提出用岩体完整性指数反映断裂构造作用对边坡稳定性的影响，具有一定的地质依据，为神经网络模型评价过程中断裂构造因素的定量化处理提供了一种思路，具有一定的实践意义。

QUANTIFICATION OF FAULT INFLUENCE FOR ANALYSIS OF SLOPE STABILITY BASED ON ARTIFICIAL NEURAL NETWORKS

Although analysis of slope stability based on artificial neural networks(ANN)has gained some significant results, it is basically limited in the stage of theory. So far it has not obtained a quite unified understanding about the selection and quantification of factors. Fault influence is ignored in most cases for it is hard to evaluate quantitatively. In this paper, Splintering Degree of Rock was taken into account in the ANN stability evaluation model of slope to evaluate the fault influence, which has definite geological basis. It is found that this method can solve the question of quantitative analysis for fault influence and improve the research of slope stability based on ANN.