Short-term solar radiation forecasting using hybrid deep residual learning and gated LSTM recurrent network with differential covariance matrix adaptation evolution …
Developing an accurate and robust prediction of long-term average global solar irradiation
plays a crucial role in industries such as renewable energy, agribusiness, and hydrology …
plays a crucial role in industries such as renewable energy, agribusiness, and hydrology …
Effective mitigation of climate change with sustainable development of energy, water and environment systems
The urgency of mitigating climate change comes with opportunities to transition society
towards a more sustainable future. Numerous options exist for immediate, deep, and …
towards a more sustainable future. Numerous options exist for immediate, deep, and …
[HTML][HTML] A review of artificial intelligence in marine science
Utilization and exploitation of marine resources by humans have contributed to the growth of
marine research. As technology progresses, artificial intelligence (AI) approaches are …
marine research. As technology progresses, artificial intelligence (AI) approaches are …
Advanced wave energy conversion technologies for sustainable and smart sea: A comprehensive review
H Li, X Shi, W Kong, L Kong, Y Hu, X Wu, H Pan… - Renewable Energy, 2024 - Elsevier
The world's oceans, covering approximately 71% of the Earth's surface, harbor vast wave
energy resources, offering a potential solution to the pressing energy crisis and …
energy resources, offering a potential solution to the pressing energy crisis and …
Forecasting electricity production from various energy sources in Türkiye: a predictive analysis of time series, deep learning, and hybrid models
When it comes to energy sources used in electricity production, the future forecasting of
electricity production from renewable energy sources is highly important for both the success …
electricity production from renewable energy sources is highly important for both the success …
[HTML][HTML] Enhancing the performance of hybrid wave-wind energy systems through a fast and adaptive chaotic multi-objective swarm optimisation method
Hybrid offshore renewable energy platforms have been proposed to optimise power
production and reduce the levelised cost of energy by integrating or co-locating several …
production and reduce the levelised cost of energy by integrating or co-locating several …
Human-cognition-inspired deep model with its application to ocean wave height forecasting
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 …
series evolution involves mixed effects of numerous factors. However, most deep models …
The motion forecasting study of floating offshore wind turbine using self-attention long short-term memory method
The motion response of a floating offshore wind turbine (FOWT) serves as a critical indicator
for the safe operation of offshore wind energy systems. It is significant to predict these …
for the safe operation of offshore wind energy systems. It is significant to predict these …
[HTML][HTML] Optimizing the hydraulic power take-off system in a wave energy converter
This study aims to determine the optimal pressure for the accumulator tank in a wave energy
converter (WEC) with hydraulic power take-off (PTO) to maximize energy generation. A …
converter (WEC) with hydraulic power take-off (PTO) to maximize energy generation. A …
A photovoltaic power prediction approach based on data decomposition and stacked deep learning model
L Liu, K Guo, J Chen, L Guo, C Ke, J Liang, D He - Electronics, 2023 - mdpi.com
Correctly anticipating PV electricity production may lessen stochastic fluctuations and
incentivize energy consumption. To address the intermittent and unpredictable nature of …
incentivize energy consumption. To address the intermittent and unpredictable nature of …