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Sunshine duration measurements and predictions in Saharan Algeria region: an improved ensemble learning approach

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Abstract

Sunshine duration is an important atmospheric indicator used in many agricultural, architectural, and solar energy applications (photovoltaics, thermal systems, and passive building design). Hence, it should be estimated accurately for areas with low-quality data or unavailable precise measurements. This paper aimed to obtain a sunshine duration measurement database in Algeria’s south region and also to study the applicability of computational models to predict them. This work develops ensemble learning models for assessing daily sunshine duration with meteorological datasets that include daily mean relative humidity, daily mean air temperature, daily maximum air temperature, daily minimum air temperature, and daily temperature range as input. The study proposes a unique hybrid model, combining grey wolf and stochastic fractal search (GWO-SFS) optimization algorithms with the random forest regressor ensemble. A pre-feature selection process improved the newly suggested model. Various commonly adopted algorithms in relevant studies have been considered as references for evaluating the new hybrid algorithm. The accuracy of models was examined as a function of some frequently used statistical pointers, as well as the Wilcoxon rank-sum test. Besides, the models were evaluated according to the several input combinations. The numerical experiments show that the proposed optimization ensemble with feature preprocessing outperforms stand-alone models in terms of prediction accuracy and robustness, where relative root mean square errors are reduced by over 20% for all considered locations. In addition, all correlation coefficients are higher than 0.999. Moreover, the proposed model, with RMSEs lower than 0.4884 hours, shows significantly superior performances compared to previously proposed models in the literature.

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Change history

  • 03 December 2021

    The word "Faculty" is redundant in affiliation 7. It should be "Faculty of Engineering" and not "FacultyFaculty of Engineering".

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Acknowledgements

We would like to thank the Algerian-Meteorological Office for providing the meteo-data.

Author information

Authors and Affiliations

  1. Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, Egypt

    El-Sayed M. El-kenawy

  2. Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura, 35712, Egypt

    El-Sayed M. El-kenawy

  3. Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt

    Abdelhameed Ibrahim

  4. Energies and Materials Research Laboratory, Faculty of Sciences and Technology, University of Tamanghasset, Tamanrasset, Algeria

    Nadjem Bailek

  5. Unité de Recherche en Energies Renouvelables en Milieu Saharien (URERMS), Centre de Développement des Energies Renouvelables (CDER), 01000, Adrar, Algeria

    Kada Bouchouicha

  6. Mechanical Power Engineering Department, Faculty of Engineering, Cairo University, Giza, Giza, 12613, Egypt

    Muhammed A. Hassan

  7. Faculty of Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan, Iran

    Mehdi Jamei

  8. Department of Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 97187, Lulea, Sweden

    Nadhir Al-Ansari

Authors
  1. El-Sayed M. El-kenawy
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  2. Abdelhameed Ibrahim
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  3. Nadjem Bailek
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  4. Kada Bouchouicha
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  5. Muhammed A. Hassan
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  6. Mehdi Jamei
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  7. Nadhir Al-Ansari
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Contributions

• El-Sayed M. El-kenawy: investigation, conceptualization, software, visualization, formal analysis, writing — original draft, and writing — review and editing

• Abdelhameed Ibrahim: methodology, conceptualization, software, visualization, formal analysis, writing — original draft, writing — review and editing, and validation

• Nadjem Bailek: conceptualization, data curation, visualization, formal analysis, writing — original draft, and writing — review and editing

• Kada Bouchouicha: conceptualization, data curation, writing — original draft, and writing — review and editing

• Muhammed A. Hassan: conceptualization, data curation, writing — original draft, and writing — review and editing

• Mehdi Jamei, resources and writing — review and editing

• Nadhir Al-Ansari: resources, writing — review and editing, and validation

Corresponding author

Correspondence to Nadjem Bailek.

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El-kenawy, ES.M., Ibrahim, A., Bailek, N. et al. Sunshine duration measurements and predictions in Saharan Algeria region: an improved ensemble learning approach. Theor Appl Climatol 147, 1015–1031 (2022). https://doi.org/10.1007/s00704-021-03843-2

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