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Geodetic deformation forecasting based on multi-variable grey prediction model and regression model

Geodetic deformation forecasting based on multi-variable grey prediction model and regression model The purpose of this paper is to examine the effectiveness of the multivariable grey prediction model in deformation forecasting.Design/methodology/approachDeformation in a dam can be seen because of many factors but without any doubt, the most influential factor is the water level. In this study, the deformation level of a point in the Keban Dam crest has been tried to be forecasted depending on the water level by the multivariable grey model GM(1,N). Regression analysis was used to test the accuracy of the prediction results obtained using the grey prediction model.FindingsThe results show that there is a great consistency between the grey prediction values and the actual values, and that the GM(1,N) produces more reliable results than the regression analysis. Based on the results, it can be concluded that the GM(1,N) is a very reliable estimation model for limited data conditions.Originality/valueDifferent from the other studies in the literature, this study investigates deformation in a dam subject to the water level in the dam reservoir. The main contribution of the study to the literature is to suggest a relatively new procedure for estimating the deformation in the dams based on the water level. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Grey Systems: Theory and Application Emerald Publishing

Geodetic deformation forecasting based on multi-variable grey prediction model and regression model

Grey Systems: Theory and Application , Volume 9 (4): 8 – Sep 30, 2019

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2043-9377
DOI
10.1108/gs-04-2019-0007
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to examine the effectiveness of the multivariable grey prediction model in deformation forecasting.Design/methodology/approachDeformation in a dam can be seen because of many factors but without any doubt, the most influential factor is the water level. In this study, the deformation level of a point in the Keban Dam crest has been tried to be forecasted depending on the water level by the multivariable grey model GM(1,N). Regression analysis was used to test the accuracy of the prediction results obtained using the grey prediction model.FindingsThe results show that there is a great consistency between the grey prediction values and the actual values, and that the GM(1,N) produces more reliable results than the regression analysis. Based on the results, it can be concluded that the GM(1,N) is a very reliable estimation model for limited data conditions.Originality/valueDifferent from the other studies in the literature, this study investigates deformation in a dam subject to the water level in the dam reservoir. The main contribution of the study to the literature is to suggest a relatively new procedure for estimating the deformation in the dams based on the water level.

Journal

Grey Systems: Theory and ApplicationEmerald Publishing

Published: Sep 30, 2019

Keywords: Grey system theory; Deformation forecasting; Multivariable grey prediction model

References