Investigation of training data selection in the black-box modeling of ship maneuvering motion

Zihao Wang, Carlos Guedes Soares & Zaojian Zou
For the identification modeling of ship maneuvering motion, comparisons between various training data are conducted to select appropriate excitation signal with maximum dynamic information, thereby ensuring the generalization ability of the identified model. The identification framework is black-box modeling based on the (“nu”)-support vector machine algorithm with radial basis function kernel, which automatically controls the number of support vectors and keeps sparsity. A Mariner class ship is taken as the study object, and the training...
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