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The potential of novel data mining models for global solar radiation prediction

  • Ahmad Sharafati
  • Khabat Khosravi
  • Payam Khosravinia
  • Kamal Ahmed
  • Saleem Abdulridha Salman
  • Zaher Mundher YaseenEmail author
  • Shamsuddin Shahid
Original Paper
  • 31 Downloads

Abstract

Advance knowledge of solar radiation is highly essential for multiple energy devotions such as sustainability in energy production and development of solar energy system. The current research investigates the capability of four data mining computation models, namely random forest (RF), random tree, reduced error pruning trees and hybrid model of random committee with random tree reduce (RC) for predicting daily measured solar radiation at four locations of Burkina Faso, i.e., Bur Dedougou, Bobo-Dioulasso, Fada-Ngourma and Ouahigouya. Daily data of seven climatic variables, namely maximum and minimum air temperature, maximum and minimum relative humidity, wind speed, evaporation and vapor pressure deficit, for the period 1998–2012 are used for solar radiation prediction. Different combinations of input variables are used according to correlation coefficient between the predictors and predictand, and the best input combination is selected based on the sensitivity of model output measured in terms of statistical indices. The obtained results are found consistence for all the meteorological stations. The highest accuracy in prediction is found when all the climate variables are used as input. The RC and RF showed the minimal absolute error in prediction at all the stations. The RMSE and NSE are found in the range of 0.03–0.05 and 0.77–0.91 for RC and 0.03–0.05 and 0.78–0.92 for RF at different stations. The results indicate that the proposed data mining models can be used for accurate prediction of solar radiation over the Burkina Faso.

Keywords

Data mining models Solar radiation prediction Climate variables Burkina Faso region 

Notes

Acknowledgments

The authors would like to reveal their gratitude and appreciation to the provider of the climatological data: The National Agency of Meteorology—Burkina Faso.

Compliance with ethical standards

Conflict of interest

There is no conflict to declare on publishing this paper.

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Copyright information

© Islamic Azad University (IAU) 2019

Authors and Affiliations

  • Ahmad Sharafati
    • 1
  • Khabat Khosravi
    • 2
  • Payam Khosravinia
    • 3
  • Kamal Ahmed
    • 4
    • 5
  • Saleem Abdulridha Salman
    • 4
  • Zaher Mundher Yaseen
    • 6
    Email author
  • Shamsuddin Shahid
    • 4
  1. 1.Department of Civil Engineering, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.Department of Watershed Management EngineeringSari Agricultural Science and Natural Resources University (SANRU)SariIran
  3. 3.Department of Water Sciences and Engineering, Faculty of AgricultureUniversity of KurdistanSanandajIran
  4. 4.School of Civil Engineering, Faculty of EngineeringUniversiti Teknologi Malaysia (UTM)Johor BahruMalaysia
  5. 5.Faculty of Water Resource ManagementLasbela University of Agriculture, Water and Marine SciencesBalochistanPakistan
  6. 6.Sustainable Developments in Civil Engineering Research Group, Faculty of Civil EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam

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