中国舰船研究2025，Vol.20Issue(1)：65-75,11.DOI:10.19693/j.issn.1673-3185.03832
基于SVR的船舶简化分离型模型水动力系数辨识研究
Hydrodynamic coefficients identification of ship simplified modular model based on support vector regression
摘要
Abstract
[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 simpli-fied three-degree-of-freedom modular models based on support vector regression(SVR).[Methods]Ini-tially,a processing strategy is introduced to enhance the effectiveness of the sample data.Further,Lasso re-gression 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]Simula-tion experiments demonstrate good agreement between the hydrodynamic coefficient forecast values and nu-merical simulation results.The calculated values of root mean square error(RMSE)and correlation coeffi-cient(CC)fall within a favorable range.[Conclusions]The SVR algorithm successfully identifies the hy-drodynamic derivatives of the modular model,the identified hydrodynamic coefficients exhibit high accuracy,and the established model demonstrates good predictive capability and robustness.关键词
船舶/操纵性/水动力学/数学模型/参数辨识/支持向量回归/白箱建模Key words
ships/maneuverability/hydrodynamics/mathematical models/parameter identification/support vector regression/white-box modelling分类
交通工程引用本文复制引用
宋利飞,王毓清,彭伟,李培勇,刘禹杉,张永峰..基于SVR的船舶简化分离型模型水动力系数辨识研究[J].中国舰船研究,2025,20(1):65-75,11.基金项目
国家自然科学基金资助项目(51809203) （51809203）
