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Prediction of Inducing Joint Opening and Closing Degree of Gravity Arch Dam Based on PCA-PSO-GRU Model
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Jie MA1, Xiao-qing LIU1, Yong-tao HUANG2
Water Resources and Power | 2023, 41(2) : 95 - 99
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Water Resources and Power | 2023, 41(2): 95-99
• DAM SAFETY AND MONITORING •
Prediction of Inducing Joint Opening and Closing Degree of Gravity Arch Dam Based on PCA-PSO-GRU Model
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Jie MA1, Xiao-qing LIU1, Yong-tao HUANG2
Affiliations
  • 1.College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
  • 2.Changjiang Design Group Co., Ltd., Wuhan 430000, China
Published: 2023-02-25 doi: 10.20040/j.cnki.1000-7709.2023.20221535
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Aiming at the problem that many measured thermometer data are not effectively used in the previous prediction of crack opening and closing time series data, and there are multiple correlations between their variables, considering the advantages of principal component analysis (PCA) in dealing with multidimensional data and gate recurrent unit (GRU) neural network in dealing with complex time series data, this paper constructed the PCA-PSO-GRU combined prediction model. Taking the monitoring data of the opening and closing of the left inducing joint of a concrete gravity arch dam as a sample, the principal components of the input variables were extracted to reduce the dimension of the input data. And then the model training and multi-step prediction were carried out. The mean absolute error and root mean square error were used to evaluate the prediction accuracy of the model. The prediction results were compared with PSOGRU, PCA-PSO-BP and the traditional statistical regression models. The results show that the PCA-PSO-GRU combined prediction model has higher accuracy in the prediction of inducing joint time series data, which can provide guidance for the evaluation of opening and closing degree of dam inducing joints.

opening and closing of inducing joint  /  PCA  /  PSO  /  GRU  /  concrete gravity arch dam  /  prediction model
Jie MA, Xiao-qing LIU, Yong-tao HUANG. Prediction of Inducing Joint Opening and Closing Degree of Gravity Arch Dam Based on PCA-PSO-GRU Model[J]. Water Resources and Power, 2023 , 41 (2) : 95 -99 . DOI: 10.20040/j.cnki.1000-7709.2023.20221535
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Year 2023 volume 41 Issue 2
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Article Info
doi: 10.20040/j.cnki.1000-7709.2023.20221535
  • Receive Date：2022-07-27
  • Online Date：2026-01-27
  • Published：2023-02-25
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  • Received：2022-07-27
  • Revised：2022-09-01
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Affiliations
    1.College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    2.Changjiang Design Group Co., Ltd., Wuhan 430000, China
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https://castjournals.cast.org.cn/joweb/sdnykx/EN/10.20040/j.cnki.1000-7709.2023.20221535
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Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
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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