文章基本信息

标题：Identification of Ship Hydrodynamic Derivatives Based on LS-SVM with Wavelet Threshold Denoising
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作者：Yi Hu ; Lifei Song ; Zuyuan Liu 等
期刊名称：Journal of Marine Science and Engineering
电子版ISSN：2077-1312
出版年度：2021
卷号：9
期号：12
页码：1356
DOI：10.3390/jmse9121356
语种：English
出版社：MDPI AG
摘要：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.