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.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price excludes VAT (USA)
Tax calculation will be finalised during checkout.
The authors confirm that all data supporting the findings of this work are available within the article.
Abada Z, Bouharkat M (2018) Study of management strategy of energy resources in Algeria. Energy Rep 4:1–7
Ahmadianfar I, Jamei M, Karbasi M, et al (2021) A novel boosting ensemble committee-based model for local scour depth around non-uniformly spaced pile groups. Eng Comput 1–23. https://doi.org/10.1007/s00366-021-01370-2
Allen RG, Pereira LS, Raes D, Smith M (1998) Table of contents originated by : agriculture crop evapotranspiration - guidelines for computing crop water requirements - FAO Irrigation and drainage paper 56. FAO - Food and Agriculture Organization of the United Nations, Rome
Almorox J, Arnaldo JA, Bailek N, Martí P (2020) Adjustment of the Angstrom-Prescott equation from Campbell-Stokes and Kipp-Zonen sunshine measures at different timescales in Spain. Renew Energy 154:337–350. https://doi.org/10.1016/j.renene.2020.03.023
Al-Tashi Q, Kadir SJA, Rais HM et al (2019) Binary optimization using hybrid grey wolf optimization for feature selection. IEEE Access 7:39496–39508
Badescu V (1999) Correlations to estimate monthly mean daily solar global irradiation: application to Romania. Energy 24:883–893
Bailek N, Bouchouicha K, EL-Shimy M, Slimani A (2017) Updated status of renewable and sustainable energy projects in Algeria. In: EL-Shimy M (ed) Economics of variable renewable sources for electric power production. Lambert Academic Publishing / Omniscriptum Gmbh & Company Kg., Germany, p 519–528
Bailek N, Bouchouicha K, Al-Mostafa Z et al (2018a) A new empirical model for forecasting the diffuse solar radiation over Sahara in the Algerian Big South. Renew Energy 117:530–537. https://doi.org/10.1016/j.renene.2017.10.081
Bailek N, Bouchouicha K, Aoun N et al (2018b) Optimized fixed tilt for incident solar energy maximization on flat surfaces located in the Algerian Big South. Sustain Energy Technol Assess 28:96–102. https://doi.org/10.1016/j.seta.2018.06.002
Bailek N, Bouchouicha K, Abdel-Hadi YA et al (2020) Developing a new model for predicting global solar radiation on a horizontal surface located in southwest region of Algeria. NRIAG J Astron Geophys 9:341–349. https://doi.org/10.1080/20909977.2020.1746892
Baker-Blocker A (1980) Ultraviolet radiation and melanoma mortality in the United States. Environ Res 23:24–28
Behrang MA, Assareh E, Ghanbarzadeh A, Noghrehabadi AR (2010) The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data. Sol Energy 84:1468–1480. https://doi.org/10.1016/j.solener.2010.05.009
Bello R, Gomez Y, Nowe A, Garcia MM (2007) Two-step particle swarm optimization to solve the feature selection problem. In: Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007). IEEE, pp 691–696. https://doi.org/10.1109/ACCESS.2021.3083593
Bouchouicha K, Hassan MA, Bailek N, Aoun N (2019) Estimating the global solar irradiation and optimizing the error estimates under Algerian desert climate. Renew Energy 139:844–858. https://doi.org/10.1016/j.renene.2019.02.071
Brown I (2013) Influence of seasonal weather and climate variability on crop yields in Scotland. Int J Biometeorol 57:605–614
Ekhmaj AI, Alwershefani MO (2017) Estimation of sunshine duration using statistical approach: Libya as a case study. Libyan J Agric 21:92–111
El-Kenawy E-SM, Eid MM, Saber M, Ibrahim A (2020a) MbGWO-SFS: modified binary grey wolf optimizer based on stochastic fractal search for feature selection. IEEE Access 8:107635–107649
El-Kenawy E-SM, Ibrahim A, Mirjalili S et al (2020b) Novel feature selection and voting classifier algorithms for COVID-19 classification in CT images. IEEE Access 8:179317–179335
El-Metwally M (2005) Sunshine and global solar radiation estimation at different sites in Egypt. J Atmos Solar-Terrestrial Phys 67:1331–1342
Essa KS, Etman SM (2004) On the relation between cloud cover amount and sunshine duration. Meteorog Atmos Phys 87:235–240
Ghoneim SSM, Farrag TA, Rashed AA, et al (2021) Adaptive dynamic meta-heuristics for feature selection and classification in diagnostic accuracy of transformer faults. IEEE Access
Gueymard CA, Myers DR (2008) Solar radiation measurement: progress in radiometry for improved modeling. In: Modeling Solar Radiation at the Earth’s Surface. Springer, Berlin Heidelberg, pp 1–27
Hassan MA, Abubakr M, Khalil A (2021a) A profile-free non-parametric approach towards generation of synthetic hourly global solar irradiation data from daily totals. Renew Energy. https://doi.org/10.1016/j.renene.2020.11.125
Hassan MA, Al-Ghussain L, Ahmad AD et al (2021b) Aggregated independent forecasters of half-hourly global horizontal irradiance. Renew Energy 181:365–383. https://doi.org/10.1016/j.renene.2021.09.060
Hassan MA, Bailek N, Bouchouicha K, Nwokolo SC (2021c) Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks. Renew Energy 171:191–209. https://doi.org/10.1016/j.renene.2021.02.103
Heddam S, Parmar K, Kisi O (2021) Comparison of the advanced machine learning methods for better prediction accuracy of solar radiation using only temperature data: a case study. Int J Energy Res. https://doi.org/10.1002/er.7341
Jervase JA, Al-Lawati A, Dorvlo ASS (2003) Contour maps for sunshine ratio for Oman using radial basis function generated data. Renew Energy 28:487–497
Jones PA, Henderson-Sellers A (1992) Historical records of cloudiness and sunshine in Australia. J Clim 5:260–267
Kaba K, Kandirmaz HM, Avci M (2017) Estimation of daily sunshine duration using support vector machines. Int J Green Energy 14:430–441. https://doi.org/10.1080/15435075.2016.1265971
Kabir MM, Shahjahan M, Murase K (2011) A new local search based hybrid genetic algorithm for feature selection. Neurocomputing 74:2914–2928
Kada B, Nadjem B, Abdelhak R et al (2020) Comparison of artificial intelligence and empirical models for energy production estimation of 20 MWp solar photovoltaic plant at the Saharan Medium of Algeria. Int J Energy Sect Manag 15:119–138. https://doi.org/10.1108/IJESM-12-2019-0017
Kandirmaz HM, Kaba K, Avci M (2014) Estimation of monthly sunshine duration in Turkey using artificial neural networks. Int J Photoenergy 2014:680596. https://doi.org/10.1155/2014/680596
Khosravi A, Koury RNN, Machado L, Pabon JJG (2018) Prediction of hourly solar radiation in Abu Musa Island using machine learning algorithms. J Clean Prod 176:63–75
Kisi O, Keshtegar B, Zounemat-Kermani M, et al (2021) Modeling reference evapotranspiration using a novel regression-based method: radial basis M5 model tree. Theor Appl Climatol 1–21
Matuszko D (2012) Influence of cloudiness on sunshine duration. Int J Climatol 32:1527–1536. https://doi.org/10.1002/joc.2370
Matuszko D (2015) A comparison of sunshine duration records from the Campbell-Stokes sunshine recorder and CSD3 sunshine duration sensor. Theor Appl Climatol 19:401–406. https://doi.org/10.1007/s00704-014-1125-z
Matuszko D, Węglarczyk S (2015) Relationship between sunshine duration and air temperature and contemporary global warming. Int J Climatol 35:3640–3653. https://doi.org/10.1002/joc.4238
Matzarakis A (2007) Assessment method for climate and tourism based on daily data. In: Matzarakis A, de Freitas CR, Scott D (eds) Developments in tourism climatology. Commission on climate, tourism and recreation. International Society of Biometeorology, Freiburg, pp 52–58
Matzarakis AP, Katsoulis VD (2006) Sunshine duration hours over the Greek region. Theor Appl Climatol 83:107–120
Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67
Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61
Mohammed T, Al-Amin AQ (2018) Climate change and water resources in Algeria: vulnerability, impact and adaptation strategy. Econ Environ Stud 18:411–429
Mohandes MA, Rehman S (2013) Estimation of sunshine duration in Saudi Arabia. J Renew Sustain Energy 5:33128
Mulyadi A, Djamal EC (2019) Sunshine duration prediction using 1D convolutional neural networks. In: 2019 6th International Conference on Instrumentation, Control, and Automation (ICA). IEEE, pp 77–81, https://doi.org/10.1109/ICA.2019.8916751
Olatomiwa L, Mekhilef S, Shamshirband S et al (2015) A support vector machine–firefly algorithm-based model for global solar radiation prediction. Sol Energy 115:632–644
Pandey M, Jamei M, Karbasi M et al (2021) Prediction of maximum scour depth near spur dikes in uniform bed sediment using stacked generalization ensemble tree-based frameworks. J Irrig Drain Eng 147:4021050
Rahimikhoob A (2014) Estimating sunshine duration from other climatic data by artificial neural network for ET 0 estimation in an arid environment. Theor Appl Climatol 118:1–8
Robaa SM (2008) Evaluation of sunshine duration from cloud data in Egypt. Energy 33:785–795
Salimi H (2015) Stochastic fractal search: a powerful metaheuristic algorithm. Knowl-Based Syst 75:1–18. https://doi.org/10.1016/j.knosys.2014.07.025
Sanchez-Lorenzo A, Calbó J, Brunetti M, Deser C (2009) Dimming/brightening over the Iberian Peninsula: trends in sunshine duration and cloud cover and their relations with atmospheric circulation. J Geophys Res Atmos 114:D00D09. https://doi.org/10.1029/2008JD011394
Trnka M, Žalud Z, Eitzinger J, Dubrovský M (2005) Global solar radiation in Central European lowlands estimated by various empirical formulae. Agric For Meteorol 131:54–76
Umoh MD, Udo SO, Udoakah Y-ON (2013) Estimation of global solar radiation on horizontal surface from sunshine hours and other meteorological parameters for Calabar, Nigeria. J Asian Sci Res 3:1083–1089
Valík A, Brázdil R, Zahradníček P et al (2019) Measurements of sunshine duration by automatic sensors and their effects on the homogeneity of long-term series in the Czech Republic. Clim Res 78:83–101. https://doi.org/10.3354/CR01564
We would like to thank the Algerian-Meteorological Office for providing the meteo-data.
We confirm that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere.
Consent to participate
We as the research team in this current contribution have voluntarily agreed to participate in this research study.
Consent for publication
We would like to give consent for the publication of identifiable details including text, material and methods, figures, and tables to be published in the Journal.
Conflict of interest
The authors declare no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
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
- Sunshine duration
- Solar energy
- Hybrid ensemble learning approach
- Algerian desert