Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation

Z Zheng, M Ali, M Jamei, Y Xiang, S Abdulla… - … and Sustainable Energy …, 2023 - Elsevier
Significant wave height is an average of the largest ocean waves, which are important for
renewable and sustainable energy resource generation. A large significant wave height can …

[HTML][HTML] A deep learning method for the prediction of ship fuel consumption in real operational conditions

M Zhang, N Tsoulakos, P Kujala, S Hirdaris - Engineering Applications of …, 2024 - Elsevier
In recent years, the European Commission and the International Maritime Organization
(IMO) implemented various operational measures and policies to reduce ship fuel …

Semantic attention and relative scene depth-guided network for underwater image enhancement

T Chen, N Wang, Y Chen, X Kong, Y Lin, H Zhao… - … Applications of Artificial …, 2023 - Elsevier
In this paper, to solve unique underwater degradation challenges covering low contrast,
color deviation and blurring, etc., a novel semantic attention and relative scene depth …

[HTML][HTML] A spectral-ensemble deep random vector functional link network for passive brain–computer interface

R Li, R Gao, PN Suganthan, J Cui, O Sourina… - Expert Systems with …, 2023 - Elsevier
Randomized neural networks (RNNs) have shown outstanding performance in many
different fields. The superiority of having fewer training parameters and closed-form …

Human-cognition-inspired deep model with its application to ocean wave height forecasting

H Wu, Y Liang, XZ Gao, P Du, SP Li - Expert Systems with Applications, 2023 - Elsevier
Ocean wave height (OWH) forecasting is indispensable but challenging task since that the
series evolution involves mixed effects of numerous factors. However, most deep models …

Benchmarking feed-forward randomized neural networks for vessel trajectory prediction

R Cheng, M Liang, H Li, KF Yuen - Computers and Electrical Engineering, 2024 - Elsevier
The burgeoning scale and speed of maritime vessels present escalating challenges to
navigational safety. Perceiving the motions of vessels, identifying anomalies, and risk …

Ship order book forecasting by an ensemble deep parsimonious random vector functional link network

R Cheng, R Gao, KF Yuen - Engineering Applications of Artificial …, 2024 - Elsevier
Efficient forecasting of ship order books holds immense significance in the maritime industry,
enabling companies to optimize their operations, allocate resources effectively, and make …

[HTML][HTML] A novel hybrid machine learning model for rapid assessment of wave and storm surge responses over an extended coastal region

SS Naeini, R Snaiki - Coastal Engineering, 2024 - Elsevier
Storm surge and waves are responsible for a substantial portion of tropical and extratropical
cyclones-related damages. While high-fidelity numerical models have significantly …

Ensemble deep learning techniques for time series analysis: a comprehensive review, applications, open issues, challenges, and future directions

M Sakib, S Mustajab, M Alam - Cluster Computing, 2025 - Springer
Time series analysis has been widely employed in various domains, including finance,
healthcare, meteorology, and economics. This approach is crucial in extracting patterns …

Revolutionizing low-carbon marine transportation: Prediction of wave energy via adaptive neuro-fuzzy inference framework in East China Sea

M Abbas, D Zhang - Arabian Journal for Science and Engineering, 2023 - Springer
Carbon neutrality hinges on effectively harnessing renewable energy sources, a critical
factor as countries worldwide enact low-carbon legislation to mitigate global warming. In this …