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A linear genetic programming approach for the prediction of solar global radiation
, Article Neural Computing and Applications ; Volume 23, Issue 3-4 , 2013 , Pages 1197-1204 ; 09410643 (ISSN) ; Saeedi Ramyani, S ; Sharif University of Technology
2013
Abstract
In this article, the linear genetic programming (LGP) is utilized to predict the solar global radiation. The solar radiation is formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years (1995-2000) in two nominal cities in Iran are used to develop LGP-based models. Separate models are established for each city. To verify the performance of the proposed models, they are applied to estimate the solar global radiation of test data of database. The contribution of the parameters affecting the solar radiation is evaluated through a sensitivity analysis. The results indicate that the LGP models give precise...
A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran
, Article Energy ; Volume 49, Issue 1 , 2013 , Pages 204-210 ; 03605442 (ISSN) ; Ramiyani, S. S ; Sarvar, R ; Moud, H. I ; Mousavi, S. M ; Sharif University of Technology
2013
Abstract
This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the...