A review on global solar radiation prediction with machine learning models in a comprehensive perspective
Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …
for economic and environmental considerations. However, because solar-radiation …
Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques
The modernisation of the world has significantly reduced the prime sources of energy such
as coal, diesel and gas. Thus, alternative energy sources based on renewable energy have …
as coal, diesel and gas. Thus, alternative energy sources based on renewable energy have …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms
This paper designs a hybridized deep learning framework that integrates the Convolutional
Neural Network for pattern recognition with the Long Short-Term Memory Network for half …
Neural Network for pattern recognition with the Long Short-Term Memory Network for half …
A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility map**
Flash flood is a typical natural hazard that occurs within a short time with high flow velocities
and is difficult to predict. In this study, we propose and validate a new soft computing …
and is difficult to predict. In this study, we propose and validate a new soft computing …
Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN …
Optimal utilisation of the sun's freely available energy to generate electricity requires efficient
predictive models of global solar radiation (GSR). These are necessary to provide solar …
predictive models of global solar radiation (GSR). These are necessary to provide solar …
[HTML][HTML] Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia
This study proposes a new hybrid deep learning (DL) model, the called CSVR, for Global
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …
Stacked LSTM sequence-to-sequence autoencoder with feature selection for daily solar radiation prediction: A review and new modeling results
We review the latest modeling techniques and propose new hybrid SAELSTM framework
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …
Deep learning and machine learning in hydrological processes climate change and earth systems a systematic review
Artificial intelligence methods and application have recently shown great contribution in
modeling and prediction of the hydrological processes, climate change, and earth systems …
modeling and prediction of the hydrological processes, climate change, and earth systems …
[HTML][HTML] Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
Global solar radiation (GSR) prediction plays an essential role in planning, controlling and
monitoring solar power systems. However, its stochastic behaviour is a significant challenge …
monitoring solar power systems. However, its stochastic behaviour is a significant challenge …