Abstract Based on the information separation of dam deformation data, we use the rescaled range method to judge the dam deformation trend, and then use the optimized extreme learning machine and chaos theory to realize the deformation prediction. The rescaled range analysis shows that the dam deformation always has positive persistence, but its degree has a weakening trend. The progressive optimization of model parameters can not only improve the prediction accuracy, but also effectively improves its stability in the process of deformation prediction, and the average relative error of the prediction model is less than 2%, which verifies the effectiveness of the prediction ideas in this paper. Compared with the dam deformation trend judgment and prediction results, it is concluded that the dam deformation will further increase, but the increase range is relatively small, and tends to be stable.
HAO Yonghe,HAO Yongyan,TANG Chengzhong et al. Research on Dam Deformation Trend Judgment and Prediction Based on Deformation Information Decomposition[J]. jgg, 2021, 41(8): 841-845.
HAO Yonghe,HAO Yongyan,TANG Chengzhong et al. Research on Dam Deformation Trend Judgment and Prediction Based on Deformation Information Decomposition[J]. jgg, 2021, 41(8): 841-845.