… The weather data used in this case study was collected from an on-site weather station located
in Tuscaloosa, Alabama, as shown in Fig. 6. Located in the southeast of the United States …

… predict daily global solar radiation data of four provinces (Kırklareli, Tokat, Nevşehir and
Karaman) which have different solar radiation … solar radiation, day length and solar radiation of …

… Solar energy forecasting represents a key element in increasing the competitiveness of solar
power plants in the energy … This paper presents an approach for predicting solar energy, …

… models for global solar radiation prediction, this paper … data from a surface meteorological
observation station, satellite-based data, numerical weather-predicting re-analyzed data) and …

… , we propose the use of deep neural networks to forecast solar radiation [24]. … forecast solar
irradiance motivated by the fact that 79% of the methods used in meteorological predictions …

… climate characteristics has a huge impact on predicting the efficiency of solar energy systems,
as well as simulations of energy … Among many weather data, solar conditions are a very …

… of data can also reflect the efficiency of the designed prediction … the solar irradiance data is
considered by using lagged data … prediction models to capture the time evolution of the data. …

… proper forecasting, this energy source cannot be trusted. For this forecasting, the use of …
This paper proposed an optimized solar radiation forecasting ensemble model consisting of …

… preferred for long-term solar irradiance forecasting [17]. In … use historical time-series data to
forecast solar irradiance in … -series data, whereas the solar irradiance time-series data is non-…

… Data reduced are considered as inputs in Elman neural network. Finally, outputs of this …
into time-domain data to forecast solar radiation by inverse PCA and DFT. Data of five areas in …