This paper explores a highly accurate identification modeling approach for the ship
maneuvering motion with fullscale trial. A multi-innovation gradient iterative (MIGI) approach …

This paper explores a novel nonparametric identification modeling technique for ship
maneuvering system. In order to solve the over-learning or under-learning problem which …

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

This work explores an adaptive moment estimation locally weighted learning (AME-LWL)
method to develop a novel high-precision non-parametric modeling technology for ship …

For off-line locally weighted learning (LWL), all training data points need to be stored in
memory, which would lead to a heavy computational burden, especially for large amount of …

Ship maneuverability prediction accuracy depends on the accuracy of ship motion model
parameter identification. To solve the problem of parameter identification of nonlinear ship …

In order to further explore more efficient identification algorithms that can solve the ship
motion identification modeling problem, a novel identification algorithm for 3-DOF ship …

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

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

This research involves a 4-DOF ship maneuvering modeling with full-scale trial data. In
order to avert the inversion of the multi-innovation matrix in the traditional multi-innovation …