[HTML][HTML] Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
[HTML][HTML] New developments in wind energy forecasting with artificial intelligence and big data: A scientometric insight
E Zhao, S Sun, S Wang - Data Science and Management, 2022 - Elsevier
Accurate forecasting results are crucial for increasing energy efficiency and lowering energy
consumption in wind energy. Big data and artificial intelligence (AI) have great potential in …
consumption in wind energy. Big data and artificial intelligence (AI) have great potential in …
[HTML][HTML] Covid-19 outbreak prediction with machine learning
Several outbreak prediction models for COVID-19 are being used by officials around the
world to make informed decisions and enforce relevant control measures. Among the …
world to make informed decisions and enforce relevant control measures. Among the …
Estimating smart energy inputs packages using hybrid optimisation technique to mitigate environmental emissions of commercial fish farms
The current study uses a hybrid optimization technique (ANN and DEA) to estimate smart
energy input packages to reduce the environmental emissions of fish farms. In 2021 …
energy input packages to reduce the environmental emissions of fish farms. In 2021 …
[HTML][HTML] Short-term nacelle orientation forecasting using bilinear transformation and ICEEMDAN framework
H Li, J Deng, P Feng, C Pu, DDK Arachchige… - Frontiers in Energy …, 2021 - frontiersin.org
To maximize energy extraction, the nacelle of a wind turbine follows the wind direction.
Accurate prediction of wind direction is vital for yaw control. A tandem hybrid approach to …
Accurate prediction of wind direction is vital for yaw control. A tandem hybrid approach to …
Short-term wind speed prediction model based on GA-ANN improved by VMD
Y Zhang, G Pan, B Chen, J Han, Y Zhao, C Zhang - Renewable energy, 2020 - Elsevier
Wind power, as a potential new energy generation technology, is gradually developing
towards to the mainstream energy in the world. However, the inherent random volatility of …
towards to the mainstream energy in the world. However, the inherent random volatility of …
Artificial neural network systems
Artificial Neural Networks is a calculation method that builds several processing units based
on interconnected connections. The network consists of an arbitrary number of cells or …
on interconnected connections. The network consists of an arbitrary number of cells or …
A short-term wind speed prediction method utilizing novel hybrid deep learning algorithms to correct numerical weather forecasting
The accuracy of the wind speed prediction is of crucial significance for the operation and
dispatch of the power grid system reasonably. However, wind speed is so random and …
dispatch of the power grid system reasonably. However, wind speed is so random and …
Short-term wind speed forecasting based on the Jaya-SVM model
Wind energy is an emerging environmentally friendly energy source. However, due to the
uncertainty and volatility of wind speed, wind energy cannot be effectively exploited, and it is …
uncertainty and volatility of wind speed, wind energy cannot be effectively exploited, and it is …
Wind speed prediction method using shared weight long short-term memory network and Gaussian process regression
Z Zhang, L Ye, H Qin, Y Liu, C Wang, X Yu, X Yin, J Li - Applied energy, 2019 - Elsevier
Wind energy has received more and more attention around the world since it is a kind of
clean, economical and renewable energy. However, the strong randomness of the wind …
clean, economical and renewable energy. However, the strong randomness of the wind …