Prediction of Hourly Solar Radiation in Six Provinces in Turkey by Artificial Neural Networks

Daily global solar radiation prediction from air temperatures using kernel extreme learning machine: A case study for Iran

“…In fact, these models presume that maximum temperature will decrease with reduced transmissivity, whilst minimum temperature will increase because of the cloud emissivity. Clear skies will increase maximum temperature due to higher shortwave radiation during sunshine hours, and minimum temperature will decrease due to higher transmissivity at night times; so the difference between daily maximum and minimum air temperatures becomes an indicator of cloudiness (Almorox et al, 2013) Estimating the horizontal global solar radiation using different artificial and computational intelligence techniques including the artificial neural network (ANN) (Tymvios et al 2005;Mubiru and Banda 2008;Şenkal and Kuleli 2009;Solmaz and Ozgoren, 2012), particle swarm optimization (PSO) (Mohandes, 2012), adaptive neuro-fuzzy inference system (ANFIS) (Mellit et al 2007;Rahoma et al, 2011;Sumithira and Kumar, 2012;Güçlü et al, 2014;Mohanty et al, 2015;Mohammadi et al, 2015a), support vector machine (SVM) (Chen et al, 2013;Mohammadi et al, 2015b;Mohammadi et al, 2015c), and etc. has received tremendous attention in recent years.…”

Application of support vector regression integrated with firefly optimization algorithm for predicting global solar radiation

“…Solmaz and Ozgoren [13] applied the artificial neural network (ANN) for determining the hourly GSR values of six selected locations in Turkey. According to their results, ANN produced proficient results in predicting solar radiation.…”

“…Furthermore, inspecting the literature exposes that a very few studies have been carried out to use the optimized SVM for the precise calculation of solar radiation [10,11,12]. Solmaz and Ozgoren [13] applied the artificial neural network (ANN) for determining the hourly GSR values of six selected locations in Turkey. According to their results, ANN produced proficient results in predicting solar radiation.…”

Prediction of solar radiation for solar systems by using ANN models with different back propagation algorithms

“…The outcome exhibited that the correlation coefficient between the ANN predictions and measured data exceeded 90%, thereby projecting a superior consistence of the model for assessment of solar radiation for locations in Nigeria. Solmaz and Ozgoren (2012) initiated the technique of artificial neural network to determine the hourly solar radiation of six chosen provinces in Turkey. According to the results, an artificial neural network model is capable for quick prediction of hourly solar radiation of the selected cities in Turkey.…”