[HTML][HTML] A review of classification problems and algorithms in renewable energy applications
Classification problems and their corresponding solving approaches constitute one of the
fields of machine learning. The application of classification schemes in Renewable Energy …
fields of machine learning. The application of classification schemes in Renewable Energy …
A novel model to predict significant wave height based on long short-term memory network
S Fan, N Xiao, S Dong - Ocean Engineering, 2020 - Elsevier
A long short-term memory (LSTM) network is proposed for the quick prediction of significant
wave height with higher accuracy than conventional neural network. The LSTM network is …
wave height with higher accuracy than conventional neural network. The LSTM network is …
Prediction and reconstruction of ocean wave heights based on bathymetric data using LSTM neural networks
C Jörges, C Berkenbrink, B Stumpe - Ocean Engineering, 2021 - Elsevier
Since climate change impacts threaten the coastal regions of the North Sea, consistent sea
state time series are essential for building coastal protection or offshore structures. Vast …
state time series are essential for building coastal protection or offshore structures. Vast …
Dynamic ensemble deep echo state network for significant wave height forecasting
Forecasts of the wave heights can assist in the data-driven control of wave energy systems.
However, the dynamic properties and extreme fluctuations of the historical observations …
However, the dynamic properties and extreme fluctuations of the historical observations …
[HTML][HTML] Towards carbon Neutrality: Prediction of wave energy based on improved GRU in Maritime transportation
Z Lv, N Wang, R Lou, Y Tian, M Guizani - Applied Energy, 2023 - Elsevier
Efficient use of renewable energy is one of the critical measures to achieve carbon
neutrality. Countries have introduced policies to put carbon neutrality on the agenda to …
neutrality. Countries have introduced policies to put carbon neutrality on the agenda to …
Multi-step forecasting of ocean wave height using gate recurrent unit networks with multivariate time series
X Li, J Cao, J Guo, C Liu, W Wang, Z Jia, T Su - Ocean Engineering, 2022 - Elsevier
Ocean wave height is an essential parameter for ocean engineering construction, planning
decisions, and coastal hazards assessment. Long-term, accurate, and reliable ocean wave …
decisions, and coastal hazards assessment. Long-term, accurate, and reliable ocean wave …
Ocean wave energy forecasting using optimised deep learning neural networks
PMR Bento, JAN Pombo, RPG Mendes, MRA Calado… - Ocean …, 2021 - Elsevier
Ocean renewable energy is a promising inexhaustible source of renewable energy, with an
estimated harnessing potential of approximately 337 GW worldwide, which could re-shape …
estimated harnessing potential of approximately 337 GW worldwide, which could re-shape …
[HTML][HTML] Application of neural networks and support vector machine for significant wave height prediction
For the purposes of planning and operation of maritime activities, information about wave
height dynamics is of great importance. In the paper, real-time prediction of significant wave …
height dynamics is of great importance. In the paper, real-time prediction of significant wave …
Forecasting tropical cyclones wave height using bidirectional gated recurrent unit
A bidirectional Gated recurrent units (BiGRU) network is proposed for the prediction of wave
height during tropical cyclones (TC). We used a data set of 28 TC events collected from 14 …
height during tropical cyclones (TC). We used a data set of 28 TC events collected from 14 …
Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
The reliable control of wave energy devices highly relies on the forecasts of wave heights.
However, the dynamic characteristics and significant fluctuation of waves' historical data …
However, the dynamic characteristics and significant fluctuation of waves' historical data …