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Prediction Method of Deep Horizontal Displacement of Slope Soil Based on Damped Holt-Winters Model

The prediction of deep horizontal displacement of slope soil is an important part of slope deformation monitoring, which has important guiding significance for the prevention of slope safety accidents. Holt-Winters model is suitable to predict the data series of deep horizontal displacement of slope soil, which show both trend growth and seasonal fluctuation. Firstly, this paper selected the data set as the original data for empirical analysis which is deep horizontal displacement of soil after pretreatment from the specific slope monitoring project, then used the Holt-winters’ damped model to perform data mining, finally, compared with the traditional prediction methods including the neural-network model and the k-nearest neighbor classification. The results show that the damped Holt-winters model has the highest prediction accuracy.