A new approach for predicting solar radiation based on a pattern search algorithm A new approach for predicting solar radiation based on a pattern search algorithm

Over the years, accurate prediction of global solar radiation (GSR) is a crucial concern for the design and planning of solar energy systems. Various academic research studies are conducted to precisely predict the GSR, particularly during the development and operational phases of solar energy syste...

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Published in:	Theoretical and applied climatology Vol. 156; no. 1; p. 31
Main Authors:	Kaplan, Yusuf Alper, Tolun, Gülizar Gizem, Kaplan, Ayşe Gül
Format:	Journal Article
Language:	English
Published:	Vienna Springer Vienna 01.01.2025 Springer Nature B.V
Subjects:	Algorithms Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Climatology Earth and Environmental Science Earth Sciences Energy Pattern search Performance evaluation power generation prediction Prediction models Predictions Radiation Search algorithms Search methods Solar energy Solar power Solar power generation Solar radiation Statistical analysis Statistical models Statistical tests System effectiveness Waste Water Technology Water Management Water Pollution Control
ISSN:	0177-798X, 1434-4483
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Abstract	Over the years, accurate prediction of global solar radiation (GSR) is a crucial concern for the design and planning of solar energy systems. Various academic research studies are conducted to precisely predict the GSR, particularly during the development and operational phases of solar energy systems. Especially, the amount of solar energy that may be generated would enhance the effectiveness of solar power generation systems and have a favourable impact on investments in solar energy systems. The pattern search algorithm (PSA) is utilised throughout multiple fields in numerous applied and engineering disciplines. Upon examining the literature, it is evident that researchers employ a broad variety of techniques and algorithms as models for predicting the GSR. However, the GSR prediction model was initially constructed using the PSA, and its performance was thoroughly evaluated through multiple statistical tests. This paper examines the performance of the pattern search method in constructing a GSR prediction model. The implementation of the PSA approach, which is rarely the primary preference in GSR prediction models, introduces originality to the study and illuminates a unique path in the literature. The acquired test outcomes were contrasted with many GSR prediction models commonly employed in the literature. The results clearly demonstrated that this technique is applicable as a GSR prediction model.
AbstractList	Over the years, accurate prediction of global solar radiation (GSR) is a crucial concern for the design and planning of solar energy systems. Various academic research studies are conducted to precisely predict the GSR, particularly during the development and operational phases of solar energy systems. Especially, the amount of solar energy that may be generated would enhance the effectiveness of solar power generation systems and have a favourable impact on investments in solar energy systems. The pattern search algorithm (PSA) is utilised throughout multiple fields in numerous applied and engineering disciplines. Upon examining the literature, it is evident that researchers employ a broad variety of techniques and algorithms as models for predicting the GSR. However, the GSR prediction model was initially constructed using the PSA, and its performance was thoroughly evaluated through multiple statistical tests. This paper examines the performance of the pattern search method in constructing a GSR prediction model. The implementation of the PSA approach, which is rarely the primary preference in GSR prediction models, introduces originality to the study and illuminates a unique path in the literature. The acquired test outcomes were contrasted with many GSR prediction models commonly employed in the literature. The results clearly demonstrated that this technique is applicable as a GSR prediction model.
ArticleNumber	31
Author	Kaplan, Yusuf Alper Kaplan, Ayşe Gül Tolun, Gülizar Gizem
Author_xml	– sequence: 1 givenname: Yusuf Alper surname: Kaplan fullname: Kaplan, Yusuf Alper email: alperkaplan@osmaniye.edu.tr organization: Department of Energy Systems Engineering, Osmaniye Korkut Ata University – sequence: 2 givenname: Gülizar Gizem surname: Tolun fullname: Tolun, Gülizar Gizem organization: Department of Energy Systems Engineering, Osmaniye Korkut Ata University – sequence: 3 givenname: Ayşe Gül surname: Kaplan fullname: Kaplan, Ayşe Gül organization: Department of Computer Science, Cukurova University
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SubjectTerms	Algorithms Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Climatology Earth and Environmental Science Earth Sciences Energy Pattern search Performance evaluation power generation prediction Prediction models Predictions Radiation Search algorithms Search methods Solar energy Solar power Solar power generation Solar radiation Statistical analysis Statistical models Statistical tests System effectiveness Waste Water Technology Water Management Water Pollution Control
Subtitle	A new approach for predicting solar radiation based on a pattern search algorithm
Title	A new approach for predicting solar radiation based on a pattern search algorithm
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