A novel adaptive hybrid-kernel function based Gaussian process regression (AHKGPR) is
proposed for nonparametric modeling of ship maneuvering motion. With the aid of Gaussian …

A novel method, Gaussian process regression optimized by genetic algorithm (GA-GPR), is
proposed for nonparametric modeling of ship maneuvering motion. A genetic algorithm with …

A fast and accurate nonparametric modeling method based on local Gaussian process
regression (LGPR) is proposed for the identification modeling and prediction of ship …

A robust and easy-to-operate method based on Gaussian process regression (GPR) is
proposed for nonparametric modeling of ship maneuvering in waves. The wave parameters …

A system identification method based on Gaussian progress regression (GPR) combined
with wavelet threshold denoising (WT) is proposed for identifying the black-box model of …

The system identification of a ship dynamics model is crucial for the intelligent navigation
and design of the ship's controller. The fluid dynamic effect and the complicated geometry of …

Black-box modeling has been widely used to predict ship maneuvering motion. A novel
black-box modeling approach using optimal mixed kernel multi-output least-squares support …

The design of maritime traffic simulators, model-based controllers, and maritime
autonomous surface ships require accurate ship dynamic models. Using different …

As a critical step designing the ship controller and the maritime traffic simulator, the system
identification of a ship dynamic model from input-output data is a promising direction …

This paper explores a fast and efficient method for identifying and modeling ship
maneuvering motion, and conducts a comprehensive experiment. Through the ship …