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Solar radiation prediction using multi-gene genetic programming approach

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Abstract

Accurate estimation of solar radiation both spatially and temporally is important for engineering studies related to climate and energy. The multi-gene genetic programming (MGGP) is proposed as a new compact method for this purpose, which is verified to yield more accurate solar radiation estimations in Turkey. Meteorological data such as extraterrestrial solar radiation, sunshine duration, mean of monthly maximum sunny hours, long-term mean of monthly maximum air temperatures, long-term mean of monthly minimum air temperatures, monthly mean air temperature, and monthly mean moisture data are selected as the MGGP model inputs. In the prediction models, the meteorological data measured from 163 stations in seven climate areas of Turkey over the period 1975–2015 are used. The MGGP model results for solar radiation prediction are found to be more accurate than the values given by some conventional empirical equations such as Abdalla, Angstrom, and Hargreaves–Samani. The performance of MGGP is also assessed for Turkey by single-data and multi-data models. The multi-data models of MGGP and the calibrated empirical equations are found to be more successful than the single-data models for solar radiation prediction.

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Acknowledgments

The authors wish to thank the Turkish State Meteorological Service for providing the long-term monthly mean of meteorological data.

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Authors and Affiliations

  1. Department of Civil Engineering, Erciyes University, Kayseri, Turkey

    Hatice Citakoglu & Nese Acanal Haktanir

  2. Department of Computer Engineering, Erciyes University, Kayseri, Turkey

    Bilal Babayigit

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  1. Hatice Citakoglu
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  2. Bilal Babayigit
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Correspondence to Hatice Citakoglu.

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Citakoglu, H., Babayigit, B. & Haktanir, N.A. Solar radiation prediction using multi-gene genetic programming approach. Theor Appl Climatol 142, 885–897 (2020). https://doi.org/10.1007/s00704-020-03356-4

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