A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO

The deformation prediction of the dam in the initial stage of operation is very important for the safety of high dams. A hybrid model integrating chaos theory, support vector machine (SVM), and an improved Grey Wolf Optimization (IGWO) algorithm is developed for deformation prediction of dam in the...

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Autores principales:	Mingjun Li, Jiangyang Pan, Yaolai Liu, Hao Liu, Junxing Wang, Zhou Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/c44eb46eb7ae41f3a59f08b8c4ad7a90
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spelling	oai:doaj.org-article:c44eb46eb7ae41f3a59f08b8c4ad7a902021-11-15T01:19:54ZA Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO1563-514710.1155/2021/8487997https://doaj.org/article/c44eb46eb7ae41f3a59f08b8c4ad7a902021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8487997https://doaj.org/toc/1563-5147The deformation prediction of the dam in the initial stage of operation is very important for the safety of high dams. A hybrid model integrating chaos theory, support vector machine (SVM), and an improved Grey Wolf Optimization (IGWO) algorithm is developed for deformation prediction of dam in the initial operation period. Firstly, the chaotic characteristics of the dam deformation time series will be identified, mainly using the Lyapunov exponent method, the correlation dimension method, and the Kolmogorov entropy method. Secondly, the SVM-IGWO model based on phase space reconstruction (PSR) is established for deformation forecasting of the dam in the initial operation period. Taking SVM as the core, the deformation time series is reconstructed in phase space to determine the input variables of SVM and the GWO algorithm is improved to realize the optimization of SVM parameters. Finally, take the actual monitoring displacement of Xiluodu super-high arch dam as an example. The engineering application example shows that, compared with the existing models, the prediction accuracy of the PSR-SVM-IGWO model established in this paper is improved.Mingjun LiJiangyang PanYaolai LiuHao LiuJunxing WangZhou ZhaoHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Mingjun Li Jiangyang Pan Yaolai Liu Hao Liu Junxing Wang Zhou Zhao A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO
description	The deformation prediction of the dam in the initial stage of operation is very important for the safety of high dams. A hybrid model integrating chaos theory, support vector machine (SVM), and an improved Grey Wolf Optimization (IGWO) algorithm is developed for deformation prediction of dam in the initial operation period. Firstly, the chaotic characteristics of the dam deformation time series will be identified, mainly using the Lyapunov exponent method, the correlation dimension method, and the Kolmogorov entropy method. Secondly, the SVM-IGWO model based on phase space reconstruction (PSR) is established for deformation forecasting of the dam in the initial operation period. Taking SVM as the core, the deformation time series is reconstructed in phase space to determine the input variables of SVM and the GWO algorithm is improved to realize the optimization of SVM parameters. Finally, take the actual monitoring displacement of Xiluodu super-high arch dam as an example. The engineering application example shows that, compared with the existing models, the prediction accuracy of the PSR-SVM-IGWO model established in this paper is improved.
format	article
author	Mingjun Li Jiangyang Pan Yaolai Liu Hao Liu Junxing Wang Zhou Zhao
author_facet	Mingjun Li Jiangyang Pan Yaolai Liu Hao Liu Junxing Wang Zhou Zhao
author_sort	Mingjun Li
title	A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO
title_short	A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO
title_full	A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO
title_fullStr	A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO
title_full_unstemmed	A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO
title_sort	deformation prediction model of high arch dams in the initial operation period based on psr-svm-igwo
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/c44eb46eb7ae41f3a59f08b8c4ad7a90
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A Deformation Prediction Model of High Arch Dams in the Initial Operation Period Based on PSR-SVM-IGWO

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