Author
A.A. Flocas
Bio: A.A. Flocas is an academic researcher from Aristotle University of Thessaloniki. The author has an hindex of 1, co-authored 1 publications receiving 62 citations.
Papers
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TL;DR: A regression analysis of the relative monthly values of global solar radiation and corresponding values of sunshine (n N ) for the period 1961-75, was performed to determine the constants a and b of the Angstrom formula, for Athens.
65 citations
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TL;DR: In this article, a graphical method to determine a and b of the modified Angstrom formula was given to determine the annual avergage (SZ) where Z is the hours of sunshine and Z the length of the day.
163 citations
TL;DR: In this article, an accurate 200 W/m2 threshold pyreheliometer instrument for measuring the duration of bright sunshine has been used to derive daily and monthly regressions for direct, diffuse, and global solar radiation component vs sunshine duration.
142 citations
TL;DR: Comparison of regression and artificial neural network models for the estimation of monthly average global solar radiations has shown that the performance values of the artificial network models are better than the regression models.
Abstract: Various models based on regression as well as artificial neural networks have been studied for the estimation of monthly average global solar radiations. Most of the regression models generally used sunshine hour data for the estimation of global solar radiations on the horizontal surfaces, whereas maximum artificial neural network models have used multilayer feed forward network sigmoid trained with Levenberg–Marquardt back propagation algorithm with different input terminals and different hidden layer neurons. Artificial neural networks have been successfully employed in solving complex problems in various fields such as function approximation, pattern association and pattern recognition, associative memories and generation of new meaningful pattern. Comparison of regression and artificial neural network models have shown that the performance values of the artificial neural network models are better than the regression models. The mean absolute percent error (MAPE) values of the artificial neural network models are lower than those of the regression models. In addition, the R values of the artificial neural network models are higher than those of regression models. The artificial neural network offers an alternative method which cannot be underestimated.
129 citations
TL;DR: A bibliographical review has been made in order to study the expressions proposed by different investigators correlating relative solar radiation (Q/Qo) with relative sunshine (n/N) with the most frequent form proposed by Angstrom in 1924 and Prescott in 1940.
116 citations
TL;DR: In this article, a one-dimensional, eddy diffusion model of lake's water temperature distribution is used to evaluate daily evaporation values as a residual of the energy budget in Lake Vegoritis in Northern Greece and for the year of 1993.
111 citations