基于灰色—BP神经网络组合模型的边坡稳定性预报方法

在前人研究成果的基础上,研究BP神经网络模型和灰色系统理论的原理,依据它们的适用条件及优缺点,对同一已知边坡取不同样本区间建立GM(1,1)模型,得到不同的预测结果。将多个灰色预测的结果作为输入变量,使用BP神经网络进行组合,输出组合预测结果。提出基于灰色神经网络范例推理的边坡稳定性评价方法,针对边坡稳定性影响因素的复杂多变性和相当强的不确定性,建立了边坡范例检索模型。通过对边坡稳定性因素的灰色模型预处理,以及边坡范例的神经网络学习,最终实现边坡稳定性评价。

Slope stability forecasting method based on Grey and BP Neutral Network combined model

Based on the studies before,BP(Back Propagation) Neural Network and Grey Theory are studied in this paper.With the using conditions,as well as the advantages and disadvantages,GM(1,1) model is established under different sample intervals of the same known slope,and different forecasting results are obtained.Using several Grey results as input data,to combine them with BP Neural Network,and then the combination results are obtained.The evaluation of slope stability forecasting is proposed based on example-inference of Grey Neural Network.According to the complicated flexible influences and strong uncertainty of slope stability,the slope example index model is set up.Finally,the current slope stability evaluation can be realized through Grey model preprocessing of the slope stability factors and Neural Network study of slope examples.