Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …
giving directions of solar energy conversion systems (design, modeling, and operation) …
Machine learning methods for solar radiation forecasting: A review
Forecasting the output power of solar systems is required for the good operation of the
power grid or for the optimal management of the energy fluxes occurring into the solar …
power grid or for the optimal management of the energy fluxes occurring into the solar …
Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales
AAA Gassar, SH Cha - Applied Energy, 2021 - Elsevier
In urban environments, decentralized energy systems from renewable photovoltaic
resources, clean and available, are gradually replacing conventional energy systems as an …
resources, clean and available, are gradually replacing conventional energy systems as an …
[HTML][HTML] Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China
Accurate estimation of global solar radiation (R s) is essential to the design and assessment
of solar energy utilization systems. Existing empirical and machine learning models for …
of solar energy utilization systems. Existing empirical and machine learning models for …
Estimation of SPEI meteorological drought using machine learning algorithms
Accurate estimation of drought events is vital for the mitigation of their adverse
consequences on water resources, agriculture and ecosystems. Machine learning …
consequences on water resources, agriculture and ecosystems. Machine learning …
A comparative study of LSTM neural networks in forecasting day-ahead global horizontal irradiance with satellite data
S Srivastava, S Lessmann - Solar Energy, 2018 - Elsevier
Accurate forecasts of solar energy are important for photovoltaic (PV) based energy plants to
facilitate an early participation in energy auction markets and efficient resource planning …
facilitate an early participation in energy auction markets and efficient resource planning …
Evaluation of electrical efficiency of photovoltaic thermal solar collector
MH Ahmadi, A Baghban, M Sadeghzadeh… - Engineering …, 2020 - Taylor & Francis
In this study, machine learning methods of artificial neural networks (ANNs), least squares
support vector machines (LSSVM), and neuro-fuzzy are used for advancing prediction …
support vector machines (LSSVM), and neuro-fuzzy are used for advancing prediction …
Day-ahead solar irradiance forecasting for microgrids using a long short-term memory recurrent neural network: A deep learning approach
In microgrids, forecasting solar power output is crucial for optimizing operation and reducing
the impact of uncertainty. To forecast solar power output, it is essential to forecast solar …
the impact of uncertainty. To forecast solar power output, it is essential to forecast solar …
Solar radiation prediction using different machine learning algorithms and implications for extreme climate events
L Huang, J Kang, M Wan, L Fang, C Zhang… - Frontiers in Earth …, 2021 - frontiersin.org
Solar radiation is the Earth's primary source of energy and has an important role in the
surface radiation balance, hydrological cycles, vegetation photosynthesis, and weather and …
surface radiation balance, hydrological cycles, vegetation photosynthesis, and weather and …
Prediction of combined terrestrial evapotranspiration index (CTEI) over large river basin based on machine learning approaches
Drought is a fundamental physical feature of the climate pattern worldwide. Over the past
few decades, a natural disaster has accelerated its occurrence, which has significantly …
few decades, a natural disaster has accelerated its occurrence, which has significantly …