Nonparametric Modelling of Ship Dynamics Using Puma Optimizer Algorithm-Optimized Twin Support Vector Regression

Ship dynamic models serve as the foundation for designing ship controllers, trajectory planning, and obstacle avoidance. Support vector regression (SVR) is a commonly used nonparametric modelling method for ship dynamics. Achieving high accuracy SVR models requires a substantial amount of training s...

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Veröffentlicht in:	Journal of marine science and engineering Jg. 12; H. 5; S. 754
Hauptverfasser:	Jiang, Lichao, Zhang, Zhi, Lu, Lingyun, Shang, Xiaobing, Wang, Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.05.2024
Schlagworte:	Accuracy Algorithms Computational efficiency Computer applications Computing time Container ships Controllers Design Dynamic models Efficiency Kalman filters Machine learning Methods Modelling nonparametric modelling Obstacle avoidance Parameter estimation Parameter identification puma optimizer algorithm Quadratic programming Regression analysis ship dynamics ship manoeuvring motion Support vector machines Training Trajectory control Trajectory planning twin support vector regression Variables White noise United Kingdom
ISSN:	2077-1312, 2077-1312
Online-Zugang:	Volltext
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