文献类型：期刊文献

英文题名：An enhanced hybrid scheme for ship roll prediction using support vector regression and TVF-EMD

作者：Xu, Dongxing[1,2,3];Yin, Jianchuan[1,2,3]

机构：[1]Guangdong Ocean Univ, Naval Architecture & Shipping Coll, Zhanjiang 524005, Peoples R China;[2]Guangdong Prov Engn Res Ctr Ship Intelligence & Sa, Zhanjiang 524005, Peoples R China;[3]Guangdong Prov Key Lab Intelligent Equipment South, Zhanjiang 524088, Peoples R China

年份：2024

卷号：307

外文期刊名：OCEAN ENGINEERING

收录：SCI-EXPANDED(收录号：WOS:001241448500001)、、EI(收录号：20242016089565)、Scopus(收录号：2-s2.0-85192848274)、WOS

基金：This work is supported by the National Natural Science Foundation of China (under Grants of 52271361 and 52231014) , the Natural Sci- ence Foundation of Guangdong Province of China (under Grant 2023A1515010684) and the Special Projects of Key Areas for Colleges and Universities of Guangdong Province (under Grant 2021ZDZX1008) .

语种：英文

外文关键词：Ship Roll Status Prediction; Hybrid Scheme; Time-Varying Filtering (TVF); Empirical Mode Decomposition (EMD); Improved Black Widow Optimization; Algorithm (IBWOA); Support Vector Regression (SVR)

外文摘要：In order to represent the complex characteristics of ship roll motion such as nonlinearity, uncertainty, and timevarying dynamics thus improving the ship roll prediction accuracy, an enhanced hybrid prediction scheme is proposed by using improved swarm intelligent optimization, time series decomposition, and machine learning. Firstly, the novel time-varying filtering-based empirical mode decomposition (TVF-EMD) is employed to decompose the ship roll motion data into multiple mode components with dynamic time-varying characteristics, which immunes of the mode mixing and intermittency problems of traditional empirical mode decomposition (EMD). Then, the support vector regression is utilized to train and predict mode components. Finally, the predicted results of individual components are reconstructed to achieve the final ship roll prediction angles. To avoid the unfavorable influence of manual parameter selection for TVF-EMD, an improved black widow optimization algorithm is employed to optimize the parameter configuration. The feasibility and effectiveness of the enhanced hybrid model are validated by ship roll prediction simulation based on the measured data of M.V. YuKun at sea. The experimental results show that the enhanced hybrid scheme can improve the prediction accuracy of ship roll motion and outrank those by using methods of EMD, ensemble empirical mode decomposition, and variational mode decomposition.