Deformation Prediction of Dam Based on Optimized Grey Verhulst Model

Changjun Huang (), Lv Zhou, Fenliang Liu, Yuanzhi Cao, Zhong Liu and Yun Xue
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Changjun Huang: School of Municipal and Surveying Engineering, Hunan City University, Yiyang 413000, China
Lv Zhou: School of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
Fenliang Liu: School of Municipal and Surveying Engineering, Hunan City University, Yiyang 413000, China
Yuanzhi Cao: School of Municipal and Surveying Engineering, Hunan City University, Yiyang 413000, China
Zhong Liu: Hunan Remote Sensing Geological Survey and Monitoring Institute, Changsha 411000, China
Yun Xue: School of Municipal and Surveying Engineering, Hunan City University, Yiyang 413000, China

Mathematics, 2023, vol. 11, issue 7, 1-15

Abstract: 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 traditional GM (1,1) model, the DGM (2,1) model, and the traditional Verhulst (1,1) model, the experimental results show that the new proposed optimized Verhulst model has higher prediction accuracy than the traditional gray model. This study offers an effective model for dealing with the non-saturated fluctuation sequence to predict dam deformation under uncertain conditions.

Keywords: Grey Verhulst model; no-saturated; deformation prediction; precision evaluation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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