Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model

Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model

When ships conduct offshore operations in the ocean, they are subject to disturbances from natural factors such as sea breezes and waves. These disturbances lead to movements detrimental to the ship’s stability, especially heave movement in the vertical direction, which profoundly impacts the safety...

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Bibliographic Details
Main Authors:	Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu
Format:	Article
Language:	English
Published:	MDPI AG 2025-05-01
Series:	Journal of Marine Science and Engineering
Subjects:	heave motion prediction long short-term memory network (LSTM) convolutional neural network (CNN) particle swarm optimization (PSO) hybrid prediction model
Online Access:	https://www.mdpi.com/2077-1312/13/6/1008
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