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A linear genetic programming approach for the prediction of solar global radiation

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An Erratum to this article was published on 15 August 2012

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 estimations of the solar global radiation and significantly outperform traditional angstrom’s model.

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Authors and Affiliations

  1. Department of Industrial Engineering, Sharif University of Technology, P.O. Box 11155-9414, Tehran, Iran

    Hassan Shavandi & Sara Saeedi Ramyani

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  1. Hassan Shavandi
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  2. Sara Saeedi Ramyani
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Correspondence to Hassan Shavandi.

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Shavandi, H., Saeedi Ramyani, S. A linear genetic programming approach for the prediction of solar global radiation. Neural Comput & Applic 23, 1197–1204 (2013). https://doi.org/10.1007/s00521-012-1039-6

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  • DOI: https://doi.org/10.1007/s00521-012-1039-6

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