边坡变形受地质、水文、气候、突发因素（如暴雨、地震）、人工活动（如开挖或防护）等各种因素的影响，这些因素与变形之间一般不是确定的定量关系。本文介绍了不同影响因素与位移量的模糊关系及位移量的模糊近似推论，在此基础上应用模糊人工神经网络进行位移量预报，并以一个边坡监测资料为例说明了具体的应用方法。 Slope deformation is affected by a variety of factors such as geology, hydrology, climate, unexpected factors (such as heavy rains and earthquakes), and artificial activities (such as excavation or protection). These factors are generally not quantitatively defined in relation to deformation. This paper introduces the fuzzy relation of different influencing factors and displacement and the fuzzy approximate deduction of displacement. Based on this, the fuzzy artificial neural network is used to predict the displacement, and a slope monitoring data is taken as an example to illustrate the specific application method.