Araştırma Makalesi

Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province

Cilt: 39 Sayı: 1 31 Mart 2025
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Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province

Öz

In this study, the performances of different models that can be used to predict global solar radiation for İzmir province were analyzed comparatively. Using ATATEK-Solar software, 14 empirical models commonly used in the literature and a newly developed AI-supported model were tested. Each model was analyzed using three different optimization algorithms (Nelder-Mead Simplex, Pattern Search, Simulated Annealing). Long-term average meteorological data obtained from Turkish State Meteorological Service were used. According to the analysis results, Model 15 performed the most successful predictions with RMSE:0.1451 and R²:0.9995 values. This was followed by Model 5 with RMSE:0.2016 and R²:0.9990 values and Model 6 with RMSE:0.2017 and R²:0.9990 values. When model performances were examined on a monthly basis, it was observed that the lowest prediction errors occurred in spring and summer months. As a result of the study, it is recommended to use Model 15 in evaluating the solar energy potential of İzmir province and system design.

Anahtar Kelimeler

Kaynakça

  1. Almorox J, Hontoria C (2004). Global solar radiation estimation using sunshine duration in Spain. Energy Conversion and Management, 45(9–10): 1529–1535. https://doi.org/10.1016/j.enconman.2003.08.022
  2. Almorox J, Bocco M, Willington E (2013). Estimation of daily global solar radiation from measured temperatures at Cañada de Luque, Córdoba, Argentina. Renewable Energy, 60: 382–387.
  3. Ampratwum DB, Dorvlo ASS (1999). Estimation of solar radiation from the number of sunshine hours. Applied Energy, 63: 161–167.
  4. Angstrom A (1924). Solar and terrestrial radiation. Report to the international commission for solar research on actinometric investigations of solar and atmospheric radiation. Quarterly Journal of the Royal Meteorological Society, 50(210): 121–126.
  5. Bristow KL, Campbell G (1984). On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agricultural and Forest Meteorology, 31(2): 159–166.
  6. Coppolino S (1994). A new correlation between clearness index and relative sunshine. Renewable Energy, 4(4): 417–423.
  7. Dogniaux R, Lemoine M (1983). Classification of radiation sites in terms of different indices of atmospheric transparency. Solar Energy Research and Development in the European Community, Series F, Vol. 2. Dordrecht, Holland: Reidel.
  8. Duffie JA, Beckman WA (2006). Solar engineering of thermal processes (3rd ed.). New York: John Wiley & Sons. Elagib N, Mansell M (2000). New approaches for estimating global solar radiation across Sudan. Energy Conversion and Management, 41(5): 419–434.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Tarımsal Enerji Sistemleri

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

24 Mart 2025

Yayımlanma Tarihi

31 Mart 2025

Gönderilme Tarihi

13 Aralık 2024

Kabul Tarihi

13 Şubat 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 39 Sayı: 1

Kaynak Göster

APA
Süslü, A. (2025). Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province. Selcuk Journal of Agriculture and Food Sciences, 39(1), 108-120. https://izlik.org/JA86LT66MB
AMA
1.Süslü A. Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province. Selcuk J Agr Food Sci. 2025;39(1):108-120. https://izlik.org/JA86LT66MB
Chicago
Süslü, Ahmet. 2025. “Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province”. Selcuk Journal of Agriculture and Food Sciences 39 (1): 108-20. https://izlik.org/JA86LT66MB.
EndNote
Süslü A (01 Mart 2025) Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province. Selcuk Journal of Agriculture and Food Sciences 39 1 108–120.
IEEE
[1]A. Süslü, “Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province”, Selcuk J Agr Food Sci, c. 39, sy 1, ss. 108–120, Mar. 2025, [çevrimiçi]. Erişim adresi: https://izlik.org/JA86LT66MB
ISNAD
Süslü, Ahmet. “Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province”. Selcuk Journal of Agriculture and Food Sciences 39/1 (01 Mart 2025): 108-120. https://izlik.org/JA86LT66MB.
JAMA
1.Süslü A. Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province. Selcuk J Agr Food Sci. 2025;39:108–120.
MLA
Süslü, Ahmet. “Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province”. Selcuk Journal of Agriculture and Food Sciences, c. 39, sy 1, Mart 2025, ss. 108-20, https://izlik.org/JA86LT66MB.
Vancouver
1.Ahmet Süslü. Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province. Selcuk J Agr Food Sci [Internet]. 01 Mart 2025;39(1):108-20. Erişim adresi: https://izlik.org/JA86LT66MB

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