基于信息扩散和BP网络的黄土边坡稳定性分析

目的探讨基于信息扩散原理的BP神经网络的黄土边坡稳定性评价模型。方法收集黄土地区24组黄土边坡实例,采用模糊信息优化处理中的信息扩散原理,建立各评价因子与安全系数之间的模糊关系,并在此基础上建立与BP神经网络相结合的评价模型。结果建立的评价模型对4组预测样本的预测结果,效果良好,较好地解决了样本过少或含有矛盾样本的问题。结论该模型在黄土边坡稳定性评价中比普通神经网络具有更高的实用性和有效性。

The evaluation of loess slope stability based on combination of information diffusion theory and BP neural metwork

Aim To establish an evaluation model of the prediction of the slope stability based on combination of information diffusion theory and BP neural network.Methods The 24 sets of slope data in loess area were collected.The fuzzy relationships between every evaluating elements and safety coefficient were established by the information diffusion principle.An evaluation model was established based on combination of information diffusion theory and BP neural network and this model can wel1 resolve the phenomenon of less practical samples,the existing contradictory samples.Results The model was verified by 4 series data of collapsing loess and the result is very good.Conclusion The result shows that the model is more useful and valid than the common neural network.