Abstract:We use singular spectrum analysis to extract the corresponding components and compute the correlation coefficients, under the influence of factors. The results show that the trend term of dam deformation mainly relates to water level and aging factor. For seasonal terms, the temperature factor contributes more than water level. Experimental results of dam deformation show that SSA can extract the trends and periodic signal effectively and is useful to forecast dam deformation. Then, recurrent forecasting method of SSA is used for the prediction of dam deformation. Compared with Gaussian process and multiple-regression analysis, the results show that SSA is an effective method with a higher predictive accuracy for analyzing and forecasting dam deformation.
ZHANG Donghua,LI Zhijuan,LIU Quanming et al. Singular Spectrum Analysis for Analyzing and Forecasting the Dam Deformation[J]. jgg, 2019, 39(10): 1081-1085.