[HTML][HTML] Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment

E Pasta, N Faedo, G Mattiazzo, JV Ringwood - Renewable and Sustainable …, 2023 - Elsevier
Currently, a significant effort in the world research panorama is focused on finding efficient
solutions to a carbon-free energy supply, wave energy being one of the most promising …

[HTML][HTML] Uncertainties in the application of artificial neural networks in ocean engineering

NP Juan, C Matutano, VN Valdecantos - Ocean Engineering, 2023 - Elsevier
Abstract Artificial Neural Networks (ANNs) are becoming more popular to model ocean
engineering problems. With the development of Artificial Intelligence, data-driven models …

Designing a multi-stage expert system for daily ocean wave energy forecasting: A multivariate data decomposition-based approach

M Jamei, M Ali, M Karbasi, Y Xiang, I Ahmadianfar… - Applied Energy, 2022 - Elsevier
Accurate forecasting of the wave energy is crucial and has significant potential because
every wave meter possesses an energy amount ranging from 30 to 40 kW along the shore …

Layout study of wave energy converter arrays by an artificial neural network and adaptive genetic algorithm

K Zhu, H Shi, M Han, F Cao - Ocean Engineering, 2022 - Elsevier
In this paper, the influence of the spatial configuration of a wave energy converter (WEC)
array upon total power output is investigated. A power prediction model has been proposed …

[HTML][HTML] Ocean energy applications for coastal communities with artificial intelligencea state-of-the-art review

Y Zhou - Energy and AI, 2022 - Elsevier
Ocean energy plays essential roles in reducing carbon emission and transforming towards
carbon neutrality, with cleaner power production, whereas the vertical cascade ocean …

Maximization of energy absorption for a wave energy converter using the deep machine learning

L Li, Z Yuan, Y Gao - Energy, 2018 - Elsevier
A controller is usually used to maximize the energy absorption of wave energy converter.
Despite the development of various control strategies, the practical implementation of wave …

[HTML][HTML] Towards real-time reinforcement learning control of a wave energy converter

E Anderlini, S Husain, GG Parker, M Abusara… - Journal of Marine …, 2020 - mdpi.com
The levellised cost of energy of wave energy converters (WECs) is not competitive with fossil
fuel-powered stations yet. To improve the feasibility of wave energy, it is necessary to …

Developing a novel hybrid Auto Encoder Decoder Bidirectional Gated Recurrent Unit model enhanced with empirical wavelet transform and Boruta-Catboost to …

M Karbasi, M Jamei, M Ali, S Abdulla, X Chu… - Journal of Cleaner …, 2022 - Elsevier
Major emphasis presently being made is on using and optimizing more sustainable and
renewable energy resources to tackle the upcoming energy demand challenges and …

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

X Guo, X Zhang, X Tian, X Li, W Lu - Applied Ocean Research, 2021 - Elsevier
Real-time motion prediction of a vessel or a floating platform can help to improve the
performance of motion compensation systems. It can also provide useful early-warning …

[HTML][HTML] Modeling of a hinged-raft wave energy converter via deep operator learning and wave tank experiments

J Zhang, X Zhao, D Greaves, S Jin - Applied Energy, 2023 - Elsevier
Abstract Model identification for a hinged-raft wave energy converter (WEC) is investigated
in this paper, based on wave tank experiments and deep operator learning. Different from …