Genetic Algorithm Based Tikhonov Regularization Method for Displacement Reconstruction

doi:10.1007/s12204-019-2060-z

Journal of Shanghai Jiao Tong University (Science) ›› 2019, Vol. 24 ›› Issue (3): 294-298.doi: 10.1007/s12204-019-2060-z

Genetic Algorithm Based Tikhonov Regularization Method for Displacement Reconstruction

PENG Zhen (彭真), YANG Zhilong (杨枝龙), TU Jiahuang* (涂佳黄)

(1. College of Civil Engineering and Mechanics, Xiangtan University, Xiangtan 411105, Hunan, China; 2. School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, Guangdong, China; 3. Hunan Key Laboratory of Geomechanics and Engineering Safety, Xiangtan University, Xiangtan 411105, Hunan, China)

出版日期:2019-06-01 发布日期:2019-05-29
通讯作者: TU Jiahuang* (涂佳黄) E-mail:tujiahuang1982@163.com

Genetic Algorithm Based Tikhonov Regularization Method for Displacement Reconstruction

PENG Zhen (彭真), YANG Zhilong (杨枝龙), TU Jiahuang* (涂佳黄)

(1. College of Civil Engineering and Mechanics, Xiangtan University, Xiangtan 411105, Hunan, China; 2. School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, Guangdong, China; 3. Hunan Key Laboratory of Geomechanics and Engineering Safety, Xiangtan University, Xiangtan 411105, Hunan, China)

Online:2019-06-01 Published:2019-05-29
Contact: TU Jiahuang* (涂佳黄) E-mail:tujiahuang1982@163.com

摘要/Abstract

摘要： In this paper, a genetic algorithm based Tikhonov regularization method is proposed for determination of globally optimal regularization factor in displacement reconstruction. Optimization mathematic models are built by using the generalized cross-validation (GCV) criterion, L-curve criterion and Engl’s error minimization (EEM) criterion as the objective functions to prevent the regularization factor sinking into the locally optimal solution. The validity of the proposed algorithm is demonstrated through a numerical study of the frame structure model. Additionally, the influence of the noise level and the number of sampling points on the optimal regularization factor is analyzed. The results show that the proposed algorithm improves the robustness of the algorithm effectively, and reconstructs the displacement accurately.

关键词: genetic algorithm, Tikhonov regularization, displacement reconstruction, inverse problem, parameter optimization

Abstract: In this paper, a genetic algorithm based Tikhonov regularization method is proposed for determination of globally optimal regularization factor in displacement reconstruction. Optimization mathematic models are built by using the generalized cross-validation (GCV) criterion, L-curve criterion and Engl’s error minimization (EEM) criterion as the objective functions to prevent the regularization factor sinking into the locally optimal solution. The validity of the proposed algorithm is demonstrated through a numerical study of the frame structure model. Additionally, the influence of the noise level and the number of sampling points on the optimal regularization factor is analyzed. The results show that the proposed algorithm improves the robustness of the algorithm effectively, and reconstructs the displacement accurately.

Key words: genetic algorithm, Tikhonov regularization, displacement reconstruction, inverse problem, parameter optimization

中图分类号:

TN 911.7

PENG Zhen (彭真), YANG Zhilong (杨枝龙), TU Jiahuang* (涂佳黄). Genetic Algorithm Based Tikhonov Regularization Method for Displacement Reconstruction[J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(3): 294-298.

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Genetic Algorithm Based Tikhonov Regularization Method for Displacement Reconstruction

Genetic Algorithm Based Tikhonov Regularization Method for Displacement Reconstruction

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