Journals / European Mechanical Science / 2018 / Cilt: 2 - Sayı: 2

Estimation of the Global Solar Radiation with the Artificial Neural Networks for the City of Sivas

Pages
46–51
Publication Date
2022-10-12
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It is believed that ANN models could be used to predict global solar radiation for locations where only the temperature and sunshine duration data are available in the city of Sivas.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, global solar radiation in the city of Sivas was estimated by artificial neural networks (ANNs) using meteorological and geographical data obtained from four different measurement stations.
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Key Findings & Data:Mean bias error (MBE), root mean square error (RMSE) and R2 ranged from -1.264 MJ/m2 to 0.938 MJ/m2, 0.710 MJ/m2 to 1.598 MJ/m2 and 0.984 to 0.994, respectively.
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Conclusion & Impact:It is believed that ANN models could be used to predict global solar radiation for locations where only the temperature and sunshine duration data are available in the city of Sivas.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Artificial neural networks · Sivas · Solar radiation

Abstract

In this study, global solar radiation in the city of Sivas was estimated by artificial neural networks (ANNs) using meteorological and geographical data obtained from four different measurement stations. Mean bias error (MBE), root mean square error (RMSE) and R2 ranged from -1.264 MJ/m2 to 0.938 MJ/m2, 0.710 MJ/m2 to 1.598 MJ/m2 and 0.984 to 0.994, respectively. It is believed that ANN models could be used to predict global solar radiation for locations where only the temperature and sunshine duration data are available in the city of Sivas.

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Cite This Article

ŞAHİN, M., GÜRLEK, C. (2022). Estimation of the Global Solar Radiation with the Artificial Neural Networks for the City of Sivas. European Mechanical Science, Cilt: 2 - Sayı: 2, 46–51. https://ajindex.com/articles/512479

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References (1)

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