Abstract
In this work one year hourly solar radiation data are analyzed and modeled. Using a 2-D surface fitting approach, a novel model is developed for the general behavior of the solar radiation. The mathematical formulation of the 2-D surface model is obtained. The accuracy of the analytical surface model is tested and compared with another surface model obtained from a feed-forward Neural Network(NN). Analytical surface model and NN surface model are compared in the sense of Root Mean Square Error (RMSE). It is obtained that the NN surface model gives more accurate results with smaller RMSE results. However, unlike the specificity of the NN surface model, the analytical surface model provides an intuitive and more generalized form that can be suitable for several other locations on earth.
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Hocaog̃lu, F.O., Gerek, Ö.N., Kurban, M. (2008). Solar Radiation Data Modeling with a Novel Surface Fitting Approach. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4985. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69162-4_48
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DOI: https://doi.org/10.1007/978-3-540-69162-4_48
Publisher Name: Springer, Berlin, Heidelberg
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