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Intelligent Optimization Support Vector Machine Model for Concrete Extra-high Arch Dam Deformation Monitoring
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Peng WANG1, Fei KANG1, Zhong-ju ZHANG2
Water Resources and Power | 2023, 41(11) : 73 - 76
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Water Resources and Power | 2023, 41(11): 73-76
• DAM SAFETY AND MONITORING •
Intelligent Optimization Support Vector Machine Model for Concrete Extra-high Arch Dam Deformation Monitoring
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Peng WANG1, Fei KANG1, Zhong-ju ZHANG2
Affiliations
  • 1.School of Hydraulic Engineering, Dalian University of Technology, Dalian 116023, China
  • 2.Sinohydro Bureau 10 Co., Ltd., Chengdu 610000, China
Published: 2023-11-25 doi: 10.20040/j.cnki.1000-7709.2023.20230211
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The arch dam deformation monitoring model is the most commonly used method for arch dam health monitoring. Aiming at the deformation monitoring problem of extra-high arch dams, this paper proposes an intelligent optimization support vector machine deformation monitoring model for concrete extra-high arch dams. Particle swarm optimization (PSO) was used to optimize the penalty factor, kernel function parameters of the support vector machine (SVM), and tolerate bias. The deformation monitoring model of concrete extra-high arch dam based on PSO-SVM was established, and the influence of aging factors on the model performance was analyzed. Engineering examples show that the PSO-SVM deformation monitoring model of concrete extra-high arch dam has good prediction accuracy and generalization ability, which is suitable for deformation monitoring of extra-high arch dam.

extra high arch dam  /  support vector machines  /  deformation monitoring  /  aging factor
Peng WANG, Fei KANG, Zhong-ju ZHANG. Intelligent Optimization Support Vector Machine Model for Concrete Extra-high Arch Dam Deformation Monitoring[J]. Water Resources and Power, 2023 , 41 (11) : 73 -76 . DOI: 10.20040/j.cnki.1000-7709.2023.20230211
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Article Info
doi: 10.20040/j.cnki.1000-7709.2023.20230211
  • Receive Date：2023-02-17
  • Online Date：2026-01-27
  • Published：2023-11-25
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History
  • Received：2023-02-17
  • Revised：2023-03-20
Funding
Affiliations
    1.School of Hydraulic Engineering, Dalian University of Technology, Dalian 116023, China
    2.Sinohydro Bureau 10 Co., Ltd., Chengdu 610000, China
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光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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