长江科学院院报2019，Vol.36Issue(4)：55-59,76,6.DOI:10.11988/ckyyb.20170944
基于LS-SVM模型的白水河滑坡台阶状位移预测
Displacement Prediction of Baishuihe Step-like Landslide by Least Square Support Vector Machine
摘要
Abstract
Landslide displacement is the most intuitive manifestation of landslide deformation, and the prediction of displacement plays a very important role in judging the evolution trend of landslide. Landslide displacement curve is a non-stationary time series affected by various factors. In this paper the trend displacement of Baishuihe landslide in the Three Gorges Reservoir is extracted by the HP filter method. Because of the nonlinear increasing characteris-tics, the trend displacement which is determined by the characteristics of the landslide is fitted and predicted by polynomial. In the meantime, induced by various factors such as evolution stages, seasonal rainfall, and water level fluctuation, the periodic displacement is trained and predicted by the model of the least squares support vector ma-chine model ( LS-SVM) . The prediction result of the cumulative displacement is the superposition of the trend term and the periodic term. The results show that the LS-SVM model has high precision in the prediction of monitoring point ZG93 and XD-04, implying that LS-SVM model is of good adaptability in predicting step-like landslide.关键词
台阶状位移/位移预测/时间序列/滤波分析/最小二乘支持向量机/趋势项/周期项/白水河滑坡Key words
step-like landslide/ displacement prediction/ time series/ filter analysis/ least squares support vector machine/ trend term/ periodic term/ Baishuihe Landslide分类
天文与地球科学引用本文复制引用
李仕波,李德营,张玉恩,李杰..基于LS-SVM模型的白水河滑坡台阶状位移预测[J].长江科学院院报,2019,36(4):55-59,76,6.基金项目
国家重点研发计划课题（2017YFC0405002）；国家自然科学基金青年基金项目（51709016）；水利部科技推广计划项目 （）
