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 **ang, 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 …

[HTML][HTML] A novel model for the study of future maritime climate using Artificial Neural Networks and Monte Carlo simulations under the context of climate change.

NP Juan, VN Valdecantos - Ocean Modelling, 2024 - Elsevier
This paper proposes a new model to study future coastal maritime climate under climate
change context. This new model combines statistical analysis, Monte Carlo simulations and …

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 …

Development of pyramid neural networks for prediction of significant wave height for renewable energy farms

A Mahdavi-Meymand, W Sulisz - Applied Energy, 2024 - Elsevier
Significant wave height (H s) is a critical parameter in the design, operation, and
maintenance of nearshore and offshore wind and wave farms. In this study, the original …

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 …

A multi-source domain feature-decision dual fusion adversarial transfer network for cross-domain anti-noise mechanical fault diagnosis in sustainable city

C Wang, H Jie, J Yang, T Gao, Z Zhao, Y Chang… - Information …, 2025 - Elsevier
Rotating machinery forms the critical backbone of infrastructure in a sustainable city, with
bearings playing a pivotal role as key mechanical transmission components. Therefore, the …

[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 …

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 …