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A state-of-the-art review of long short-term memory models with applications in hydrology and water resources
Z Feng, J Zhang, W Niu - Applied Soft Computing, 2024 - Elsevier
Abstract Long Short-Term Memory (LSTM) has recently emerged as a crucial tool for
scientific research in hydrology and water resources. Despite its widespread use, a …
scientific research in hydrology and water resources. Despite its widespread use, a …
Artificial neural networks for photovoltaic power forecasting: a review of five promising models
Solar energy is largely dependent on weather conditions, resulting in unpredictable,
fluctuating, and unstable photovoltaic (PV) power outputs. Thus, accurate PV power …
fluctuating, and unstable photovoltaic (PV) power outputs. Thus, accurate PV power …
A novel WaveNet-GRU deep learning model for PEM fuel cells degradation prediction based on transfer learning
Abstract Precise prediction of Remaining Useful Life (RUL) within the transportation industry
is essential for cost reduction and enhanced energy efficiency, focusing on extending the …
is essential for cost reduction and enhanced energy efficiency, focusing on extending the …
A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation
Small-scale distributed energy systems with combined cooling, heating, and power (DES-
CCHP) production have attracted international interest. However, fluctuating loads and …
CCHP) production have attracted international interest. However, fluctuating loads and …
InfoCAVB-MemoryFormer: Forecasting of wind and photovoltaic power through the interaction of data reconstruction and data augmentation
Rare or missing data pose significant challenges in the prediction of wind power (WP) and
photovoltaic power (PV). Many methods address the data scarcity issue solely through …
photovoltaic power (PV). Many methods address the data scarcity issue solely through …
Power system flexibility analysis using net-load forecasting based on deep learning considering distributed energy sources and electric vehicles
Today, wind and solar energy sources have opened their place in the power system due to
their environmental appeal. With the presence of these renewable energy sources (RESs) …
their environmental appeal. With the presence of these renewable energy sources (RESs) …
Short-term PV power data prediction based on improved FCM with WTEEMD and adaptive weather weights
Photovoltaic (PV) systems are commonly used in zero energy buildings (ZEBs) due to their
high efficiency and convenience. However, PV systems are affected by meteorological …
high efficiency and convenience. However, PV systems are affected by meteorological …
An interpretable hybrid spatiotemporal fusion method for ultra-short-term photovoltaic power prediction
B Gong, A An, Y Shi, H Guan, W Jia, F Yang - Energy, 2024 - Elsevier
For a long time, fossil fuels have been the primary source for meeting energy demands and
driving economic growth worldwide [[1],[2],[3]]. However, in recent years, the negative …
driving economic growth worldwide [[1],[2],[3]]. However, in recent years, the negative …
Water resource management and flood mitigation: hybrid decomposition EMD-ANN model study under climate change
The growing population and the rise in urbanization have made managing water a critical
concern around the world in recent years. Globally, flooding is one of the most devastating …
concern around the world in recent years. Globally, flooding is one of the most devastating …
Spectral-temporal convolutional approach for PV systems output power forecasting: Case studies in single-site and multi-site
Accurate predictions of photovoltaic (PV) and wind power outputs are indispensable for
integrating additional renewable energy sources into the grid. Photovoltaic energy is …
integrating additional renewable energy sources into the grid. Photovoltaic energy is …