Multipoint Heave Motion Prediction Method for Ships Based on the PSO-TGCN Model

作     者：DING Shi-feng MA Qun ZHOU Li HAN Sen DONG Wen-bo DING Shi-feng;MA Qun;ZHOU Li;HAN Sen;DONG Wen-bo

作者机构：School of Naval Architecture and Ocean EngineeringJiangsu University of Science and TechnologyZhenjiang 212003China School of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China 

出 版 物：《China Ocean Engineering》 (中国海洋工程（英文版）)

年 卷 期：2023年第37卷第6期

页      面：1022-1031页

核心收录：

学科分类：08[工学] 0824[工学-船舶与海洋工程] 082401[工学-船舶与海洋结构物设计制造] 

基　　金：financially supported by the National Key Research and Development Program of China (Grant No.2022YFE010700) the National Natural Science Foundation of China (Grant No.52171259) the High-Tech Ship Research Project of Ministry of Industry and Information Technology (Grant No.342) Foundation of State Key Laboratory of Ocean Engineering in Shanghai Jiao Tong University (Grant No.GKZD010086-2) 

主　　题：ship motion prediction time delay multipoint forecast time-graph convolutional neural network particle swarm optimization 

摘      要：During ship operations,frequent heave movements can pose significant challenges to the overall safety of the ship and completion of cargo *** existing heave compensation systems suffer from issues such as dead zones and control system time lags,which necessitate the development of reasonable prediction models for ship heave *** this paper,a novel model based on a time graph convolutional neural network algorithm and particle swarm optimization algorithm(PSO-TGCN)is proposed for the first time to predict the multipoint heave movements of ships under different sea *** enhance the dataset s suitability for training and reduce interference,various filter algorithms are employed to optimize the *** training process utilizes simulated heave data under different sea conditions and measured heave data from multiple *** results show that the PSO-TGCN model predicts the ship swaying motion in different sea states after 2 s with 84.7%accuracy,while predicting the swaying motion in three different *** performing a comparative study,it was also found that the present method achieves better performance that other popular *** model can provide technical support for intelligent ship control,improve the control accuracy of intelligent ships,and promote the development of intelligent ships.