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Identification of Ship Hydrodynamic Derivatives Based on LS-SVM with Wavelet Threshold Denoising

Yi Hu; Lifei Song; Zuyuan Liu; Jianxi Yao
Journal of Marine Science and Engineering · Vol. 9, Issue 12 · pp. 1356 · 2021

Abstract

Nowadays, system-based simulation is one of the main methods for ship manoeuvring prediction. Great efforts are usually devoted to the determination of hydrodynamic derivatives as required for the mathematical models used for such methods. System identification methods can be applied to determine hydrodynamic derivatives. The purpose of this work is to present a parameter identification study based on least-squares support-vector machines (LS-SVMs) to obtain hydrodynamic derivatives for an Abkowitz-type model. An approach for constructing training data is used to reduce parameter drift. In addition, wavelet threshold denoising is applied to filter out the noise from the sample data during data pre-processing. Most of the resulting derivatives are very close to the original ones—especially for linear derivatives. Although the errors of high-order derivatives seem large, the final predicted results of the turning circle and zigzag manoeuvres agree pretty well with the reference ones. This indicates that the used methods are effective in obtaining manoeuvring hydrodynamic derivatives.

Bibliographic Information

JournalJournal of Marine Science and Engineering
PublisherMDPI
Publication Date2021-12-01
Publication Year2021
Volume9
Issue12
Pages1356
Document TypeJournal Article
eISSN2077-1312
DOI10.3390/jmse9121356
SubjectMarine science; oceanography; marine engineering; coastal science; marine environment

Access Information

NARA Access CoverageOA / free full text
Journal Homepagehttps://www.mdpi.com/journal/jmse
Publisher PageOpen Publisher Page
This article is openly available from the publisher.