Artificial intelligence for management of variable renewable energy systems: a review of current status and future directions
This review paper provides a summary of methods in which artificial intelligence (AI)
techniques have been applied in the management of variable renewable energy (VRE) …
techniques have been applied in the management of variable renewable energy (VRE) …
[HTML][HTML] Assessment and prediction of significant wave height using hybrid CNN-BiLSTM deep learning model for sustainable wave energy in Australia
Wave energy is regarded as one of the powerful renewable energy sources and depends on
the assessment of significant wave height (H s) for feasibility. Hence, this study explores the …
the assessment of significant wave height (H s) for feasibility. Hence, this study explores the …
Comment on Papers using Machine Learning for Significant Wave Height Time Series Prediction: Complex Models Do Not Outperform Auto-regression
H Jiang, Y Zhang, C Qian, X Wang - Ocean Modelling, 2024 - Elsevier
Abstract Significant Wave Height (SWH) is crucial in many aspect of ocean engineering. The
accurate prediction of SWH has therefore been of immense practical value. Recently …
accurate prediction of SWH has therefore been of immense practical value. Recently …
Missing data recovery of wind speed in wind farms: A spatial-temporal tensor decomposition approach
H Tan, S Lin, X Xu, P Shi, R Li, S Wang - Journal of Renewable and …, 2023 - pubs.aip.org
Missing data recovery plays a critical role in improving the data quality of wind speed in wind
farms, and numerous methods have been proposed to address this issue. However, most of …
farms, and numerous methods have been proposed to address this issue. However, most of …
SWSA transformer: a forecasting method of ultra-short-term wind speed from an offshore wind farm using global attention mechanism
S Lin, J Wang, X Xu, H Tan, P Shi, R Li - Journal of Renewable and …, 2023 - pubs.aip.org
Accurate ultra-short-term wind speed forecasting is great significance to ensure large scale
integration of wind power into the power grid, but the randomness, instability, and non-linear …
integration of wind power into the power grid, but the randomness, instability, and non-linear …
Carbon peak management strategies for achieving net-zero emissions in smart buildings: Advances and modeling in digital twin
Q Wang, Y Yin, Y Chen, Y Liu - Sustainable Energy Technologies and …, 2024 - Elsevier
This research employs the Modified differential evolution (DE) algorithm and incorporates
Random Forest Regression for forecasting renewable energy. The primary emphasis is on …
Random Forest Regression for forecasting renewable energy. The primary emphasis is on …
Optimized deep learning modelling for predicting the diffusion range and state change of filling projects
Z Xu, A Che, H Zhou, Y Shen, W He - Tunnelling and Underground Space …, 2024 - Elsevier
Concealment of filling constructions poses significant challenges for quality assurance in
filling engineering. Direct surveillance of fill dispersal currently remains infeasible, while …
filling engineering. Direct surveillance of fill dispersal currently remains infeasible, while …
[HTML][HTML] Generalized machine learning models to predict significant wave height utilizing wind and atmospheric parameters
Significant wave height (SWH) is a key parameter for wave energy extraction, ship
navigation, oil and gas extraction, coastal structure construction, etc. Direct measurements of …
navigation, oil and gas extraction, coastal structure construction, etc. Direct measurements of …
[HTML][HTML] Transformation of significant wave height and set-up due to entrained air bubbles effect in breaking waves
MN Hossain, S Araki - Ocean Modelling, 2024 - Elsevier
The transformation of wave height is of paramount significance in coastal engineering and
the design of coastal structures. Considering the influence of air bubbles, this study devised …
the design of coastal structures. Considering the influence of air bubbles, this study devised …