An APSO-based TPA-BLSTM model for predicting ship motion in irregular waves using wave-series input-Reference-Cited by-同舟云学术

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An APSO-based TPA-BLSTM model for predicting ship motion in irregular waves using wave-series input

Published:2024-04-03 Issue: Volume: Page:1-12
ISSN:1744-5302
Container-title:Ships and Offshore Structures
language:en
Short-container-title:Ships and Offshore Structures

Author:

Xue Jiansheng¹²,Gao Zhiliang¹²,Yi Wenhai³

Affiliation:

1. Key Laboratory of High Performance Ship Technology (Wuhan University of Technology), Ministry of Education, Wuhan, People’s Republic of China

2. School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan, People’s Republic of China

3. PowerCHINA Offshore Wind Power Engineering Co., Ltd, Haikou, People’s Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17445302.2024.2336675

Reference27 articles.

1. Measurements of short water waves using stereo matched image sequences

2. Duan S, Ma Q, Huang L, Ma X. 2019. A LSTM deep learning model for deterministic ship motions estimation using wave-excitation inputs. In: The 29th international ocean and polar engineering conference, Honolulu. p. 16–21.

3. A hybrid AR-EMD-SVR model for the short-term prediction of nonlinear and non-stationary ship motion

4. Predicting heave and surge motions of a semi-submersible with neural networks

5. Long Short-Term Memory

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