Machine learning for naval architecture, ocean and marine engineering

JP Panda - Journal of Marine Science and Technology, 2023 - Springer
Abstract Machine learning (ML)-based techniques have found significant impact in many
fields of engineering and sciences, where data-sets are available from experiments and …

PAOLTransformer: Pruning-adaptive optimal lightweight Transformer model for aero-engine remaining useful life prediction

X Zhang, J Sun, J Wang, Y Jin, L Wang, Z Liu - Reliability Engineering & …, 2023 - Elsevier
Abstracts Aero-engines are core equipment in aerospace field, and their remaining useful
life (RUL) prediction is a critical aspect in spacecraft monitoring and maintenance …

A machine-learning approach based on attention mechanism for significant wave height forecasting

J Shi, T Su, X Li, F Wang, J Cui, Z Liu… - Journal of Marine Science …, 2023 - mdpi.com
Significant wave height (SWH) is a key parameter for monitoring the state of waves. Accurate
and long-term SWH forecasting is significant to maritime shipping and coastal engineering …

ASTMEN: an adaptive spatiotemporal and multi-element fusion network for ocean surface currents forecasting

X Li, F Wang, T Song, F Meng, X Zhao - Frontiers in Marine Science, 2023 - frontiersin.org
Accurate forecasting of ocean surface currents is crucial for the planning of marine activities,
including fisheries, shipping, and pollution control. Previous studies have often neglected …

Ocean current prediction using the weighted pure attention mechanism

J Liu, J Yang, K Liu, L Xu - Journal of Marine Science and Engineering, 2022 - mdpi.com
Ocean current (OC) prediction plays an important role for carrying out ocean-related
activities. There are plenty of studies for OC prediction with deep learning to pursue better …

Forecasting vertical profiles of ocean currents from surface characteristics: A multivariate multi-head convolutional neural network–long short-term memory approach

S Kar, JR McKenna, G Anglada, V Sunkara… - Journal of Marine …, 2023 - mdpi.com
While study of ocean dynamics usually involves modeling deep ocean variables, monitoring
and accurate forecasting of nearshore environments is also critical. However, sensor …

Spatio–temporal attention-based deep learning framework for mesoscale eddy trajectory prediction

X Wang, C Li, X Wang, L Tan… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Accurate prediction of mesoscale eddy trajectories requires efficient models with large-size
available data instances to capture the main eddy characteristics. However, there is a lack of …

A deep learning model for forecasting velocity structures of the loop current system in the gulf of mexico

A Muhamed Ali, H Zhuang, J VanZwieten, AK Ibrahim… - Forecasting, 2021 - mdpi.com
Despite the large efforts made by the ocean modeling community, such as the GODAE
(Global Ocean Data Assimilation Experiment), which started in 1997 and was renamed as …

[HTML][HTML] Node Adjustment Scheme of Underwater Wireless Sensor Networks Based on Motion Prediction Model

H Zheng, H Chen, A Du, M Yang, Z Jin… - Journal of Marine Science …, 2024 - mdpi.com
With the wide application of Underwater Wireless Sensor Networks (UWSNs) in various
fields, more and more attention has been paid to deploying and adjusting network nodes. A …

Analysis of roll center compensation method for underwater gliders based on deep learning

C Wang, Y Wang, R Zhang, W Niu - Ocean Engineering, 2022 - Elsevier
Underwater glider (UG) is one of the most promising low-power and long-voyage
autonomous ocean observation platforms. During the gliding, the roll regulation unit (RRU) …