关键词: 混沌时间序列 , 相空间重构 , Lyapunov 指数 , 边坡位移预测

Abstract: According to the nonlinear characteristics of slope displacement-time series , the information offered by the time series datum sets can be fully exploited and the trend of slope displacement evolution can be precisely predicted by making real-time forecasting based on phase space reconstruction. The method of local function approximation and the prediction based on Lyapunov exponents are discussed in this paper. The examples suggest that the methods based on phase space reconstruction are more accurate and more adaptable than the decomposition model of non-stationary time series.

Key words: chaotic time series ;phase space reconstruction , Lyapunov exponents , shope displacement forecasting