Intelligent prediction of excess pore water pressure of seabed around double pile foundation under the action of regular wave

Hou Jiankang; Cheng Yongzhou; Wang Dunge; Han Xiaorui; Li Yuanlong; Shi Yi

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Hou Jiankang，Cheng Yongzhou，Wang Dunge, et al. Intelligent prediction of excess pore water pressure of seabed around double pile foundation under the action of regular wave[J]. Haiyang Xuebao，2026, 48(x)：1–13

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Intelligent prediction of excess pore water pressure of seabed around double pile foundation under the action of regular wave

1.
School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410114, China
2.
Key Laboratory of Water-Sediment Sciences and Water Disaster Prevention of Hunan Province, Changsha 410114, China

Received Date: 2026-03-08
Rev Recd Date: 2026-05-12

Available Online: 2026-05-22

Abstract

Abstract

This study conducted multi-objective intelligent prediction research on the super-pore water pressure around double-pile foundations in the seabed under wave action. Firstly, the time-history evolution and spatial distribution of excess pore water pressure around the double-pile foundation under different wave heights are analyzed by wave flume test. Secondly, the phase lag detection and dynamic alignment method are used to preprocess the data, and GRU and ELM neural networks are used for training prediction respectively. Finally, the dynamic error preferred fusion method is used to fuse the outputs of the two models. The results show that under the current test conditions, with the increase of wave height, the amplitude of excess pore water pressure in the seabed around the double-pile foundation increases significantly, showing obvious amplitude attenuation and phase lag along the depth direction, and there are obvious spatial differences in the maximum amplitude of excess pore water pressure around the double-pile foundation. In addition, the constructed fusion model performs best compared with the original model or single model evaluation metrics, where PCC is 0.9827, NSE is 0.9218, RMSE is 0.3305%, and MAE is 0.2559%. The research results provide an effective way for the intelligent prediction of multi-objective pore pressure of seabed around pile foundation under wave action.
- double pile foundation,
- excess pore water pressure,
- phase lag detection,
- dynamic error,
- fusion model

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References(29)

References

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