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RETRACTED ARTICLE: Potential of support vector regression for solar radiation prediction in Nigeria

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  • Lanre Olatomiwa

    (University of Malaya
    Federal University of Technology)

  • Saad Mekhilef

    (University of Malaya)

  • Shahaboddin Shamshirband

    (University of Malaya)

  • Dalibor Petkovic

    (University of Niš)

Abstract

In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taking from Iseyin meteorological station in Nigeria was examined. The process, which simulates the solar radiation with support vector regression (SVR), was constructed. The inputs were monthly mean maximum temperature (Tmax), monthly mean minimum temperature (Tmin) and monthly mean sunshine duration ( $$ \bar{n} $$ n ¯ ). Polynomial and radial basis functions (RBF) are applied as the SVR kernel function to estimate solar radiation. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR with polynomial basis function compared to RBF. The SVR coefficient of determination R 2 with the polynomial function was 0.7395 and with the radial basis function, the R 2 was 0.5877.

Suggested Citation

  • Lanre Olatomiwa & Saad Mekhilef & Shahaboddin Shamshirband & Dalibor Petkovic, 2015. "RETRACTED ARTICLE: Potential of support vector regression for solar radiation prediction in Nigeria," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 1055-1068, June.
  • Handle: RePEc:spr:nathaz:v:77:y:2015:i:2:d:10.1007_s11069-015-1641-x
    DOI: 10.1007/s11069-015-1641-x
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    1. Lanre Olatomiwa & Saad Mekhilef & Shahaboddin Shamshirband & Dalibor Petkovic, 2020. "Retraction Note to: Potential of support vector regression for solar radiation prediction in Nigeria," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3865-3866, September.

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