关键词: 位移预测, 滞后性, 诱发因素, 树坪滑坡, 三峡库区

Abstract: In view of the lag effect of inducing factors on displacement and deformation of landslides, the Mean Impact Value (MIV) method is used to screen the inducing factors for different lag phases, and then the hybrid MIV-GRNN model is set to predict the landslide displacement combined with the Generalized Regression Neural Network (GRNN). Taking Shuping Landslide in Three Gorges Reservoir area as an example, the time series of landslide displacement is decomposed into trend term and periodic term, and the polynomial and MIV-GRNN models are used to predict the trend term and periodic term displacement respectively. The results show that MIV-GRNN model can well reflect the lag influences of inducing factors on landslide displacement. Compared with the traditional prediction model, the maximum relative error is reduced by 11.2%.

Key words: displacement prediction, lag effect, inducing factor, Shuping Landslide, Three Gorges Reservoir area