Solar Radiation Modeling for Turkey Using Atmospheric Parameters with Artificial Neural Networks
نویسنده
چکیده
Artificial neural network (ANN) method was applied for modeling and prediction of mean solar radiation in given atmospheric parameters (temperature, pressure, humidity, precipitable water and month) in Turkey (26–45oE and 36–42oN) during the period of 2004–2006. Levenberg-Marquardt (LM) learning algorithms and logistic sigmoid transfer function were used in the network. In order to train the network, meteorological measurements taken by the Turkish State Meteorological Service (TSMS) and Wyoming University for the period from 2004 to 2006 from five stations (Adana, Ankara, İstanbul, İzmir, Samsun) distributed in Turkey were used as training and testing data. Data from years 2004 and 2005 were used for training, while the year 2006 was used for testing and validating the model. Solar radiation is the output.
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