The present work was supported by natural science foundation of Hunan province of China (Grant No. 2021JJ30076, 2022JJ50261) and foundation of Hunan educational committee (Grant No. 21A0502).
机构署名：
本校为第一机构
院系归属：
市政与测绘工程学院
摘要：
Dam deformation monitoring data are generally characterized by non-smooth and no-saturated S-type fluctuation. The grey Verhulst model can get better results only when the data series is non-monotonic swing development and the saturated S-shaped sequence. Due to the limitations of the grey Verhulst model, the prediction accuracy will be limited to a certain extent. Aiming at the shortages in the prediction based on the traditional Verhulst model, the optimized grey Verhulst model is proposed to improve the prediction accuracy of the dam deformation monitoring. Compared with those of the tradit...
