Chinese Journal of Ship Research, Volume. 20, Issue 1, 65(2025)

Hydrodynamic coefficients identification of ship simplified modular model based on support vector regression

Lifei SONG1...2, Yuqing WANG1,2, Wei PENG3, Peiyong LI1,2, Yushan LIu4 and Yongfeng ZHANG5 |Show fewer author(s)
Author Affiliations
  • 1Key Laboratory of High Performance Ship Technology (Wuhan University of Technology), Ministry of Education, Wuhan 430063, China
  • 2School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China
  • 3Guangzhou Shipyard International Co. Ltd., Guangzhou 511462, China
  • 4The 92942 Unit of PLA, Beijing 100055, China
  • 5Wuhan University of Technology, Wuhan 430070, China
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    Objectives

    To address the issue of multicollinearity and parameter drift in the identification of hydrodynamic coefficients in ship separated-type models, this paper proposes a method for modeling simplified three-degree-of-freedom modular models based on support vector regression (SVR).

    Methods

    Initially, a processing strategy is introduced to enhance the effectiveness of the sample data. Further, Lasso regression is introduced to select the most influential hydrodynamic coefficients and alleviate multicollinearity. Subsequently, a regression model for the identification of hydrodynamic derivatives is derived for the MMG model. A data centralization and differencing method is then employed to reconstruct the regression model, mitigating the impact of parameter drift on hydrodynamic derivative identification errors.

    Results

    Simulation experiments demonstrate good agreement between the hydrodynamic coefficient forecast values and numerical simulation results. The calculated values of root mean square error (RMSE) and correlation coefficient (CC) fall within a favorable range.

    Conclusions

    The SVR algorithm successfully identifies the hydrodynamic derivatives of the modular model, the identified hydrodynamic coefficients exhibit high accuracy, and the established model demonstrates good predictive capability and robustness.

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    Lifei SONG, Yuqing WANG, Wei PENG, Peiyong LI, Yushan LIu, Yongfeng ZHANG. Hydrodynamic coefficients identification of ship simplified modular model based on support vector regression[J]. Chinese Journal of Ship Research, 2025, 20(1): 65

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    Paper Information

    Category: Maneuverability Forecast

    Received: Mar. 19, 2023

    Accepted: --

    Published Online: Mar. 13, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.03832

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