滑坡地下水位动态预测的径向基函数法

PREDICTION OF GROUNDWATER LEVEL IN LANDSLIDES BASED ON RADIAL BASIS FUNCTION

滑坡地下水系统是一个复杂的水系统,地下水位的预测是根据地下水位与其影响因素之间存在的映射关系,寻求滑坡稳定性分析所需的地下水边界条件,以较为准确地反映地下水的变化对滑坡体稳定性的影响。通过对基于径向基函数网络模型的分析,建立了适合于滑坡地下水位预测的神经网络预测模型,并将其用于地下水位的动态预测。实例表明,该方法预测精度较高,具有一定的推广价值。

The groundwater system in landslides is a complicated one influenced by many factors. According to the relation between groundwater level and the factors that affect the variation of groundwater level in landslides, the first purpose of groundwater prediction is to find out the reasonable boundary condition that is basis for stability analysis of landslides. The second purpose of prediction is to find out the variation of stability coefficient versus groundwater level. For these purposes, artificial neural network model which adopts radial basis function is developed, based on the relationship between groundwater level and its influential factors used for the prediction of groundwater regime. Case study indicates that the precision of the developed model is rather high and its popularization significance is better than the others models.