Prediction of Solar Ultraviolet Radiations Using Random Matrix Theory

Purpose: The correlation of different samples can be described by analytical models such as random matrix theory. In this study, we tried to describe the correlation of different types of ultraviolet values in different months, weeks, and hours to get a significant relationship of special times, whi...

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Published inFrontiers in biomedical technologies Vol. 11; no. 1
Main Authors Malekzadeh, Reza, Seidi, Masoud, Asadpour, Nikan, Sabri, Hadi
Format Journal Article
LanguageEnglish
Published Tehran University of Medical Sciences 01.12.2024
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ISSN2345-5837
2345-5837
DOI10.18502/fbt.v11i1.14505

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Abstract Purpose: The correlation of different samples can be described by analytical models such as random matrix theory. In this study, we tried to describe the correlation of different types of ultraviolet values in different months, weeks, and hours to get a significant relationship of special times, which one needs to get enough intensity of the sun or avoid getting sunburn. Materials and Methods: To this aim, we focused on the hourly and daily mean amounts of ultraviolet A, B, and C intensities of solar radiation in Tabriz urban area were measured during a full year of 2017-2018. We used such ultraviolet values which are measured at the same hour of the day to satisfy the same symmetry criteria which are necessary in random matrix theory. These data are unfolded and classified in different sequences to analyze in the nearest neighbor spacing distribution framework via the maximum likelihood estimation technique. Results: Strong correlation is yielded for daily values of UVA in comparison with the other types of ultraviolet radiations. Also, we considered the dependence of correlation degrees of these three types of ultraviolet to average temperature and humidity at different months. Conclusion: The results propose more correlation of UVA indices in August while such correlation of UVC radiations are yielded in December.
AbstractList Purpose: The correlation of different samples can be described by analytical models such as random matrix theory. In this study, we tried to describe the correlation of different types of ultraviolet values in different months, weeks, and hours to get a significant relationship of special times, which one needs to get enough intensity of the sun or avoid getting sunburn. Materials and Methods: To this aim, we focused on the hourly and daily mean amounts of ultraviolet A, B, and C intensities of solar radiation in Tabriz urban area were measured during a full year of 2017-2018. We used such ultraviolet values which are measured at the same hour of the day to satisfy the same symmetry criteria which are necessary in random matrix theory. These data are unfolded and classified in different sequences to analyze in the nearest neighbor spacing distribution framework via the maximum likelihood estimation technique. Results: Strong correlation is yielded for daily values of UVA in comparison with the other types of ultraviolet radiations. Also, we considered the dependence of correlation degrees of these three types of ultraviolet to average temperature and humidity at different months. Conclusion: The results propose more correlation of UVA indices in August while such correlation of UVC radiations are yielded in December.
Purpose: The correlation of different samples can be described by analytical models such as random matrix theory. In this study, we tried to describe the correlation of different types of ultraviolet values in different months, weeks, and hours to get a significant relationship of special times, which one needs to get enough intensity of the sun or avoid getting sunburn. Materials and Methods: To this aim, we focused on the hourly and daily mean amounts of ultraviolet A, B, and C intensities of solar radiation in Tabriz urban area were measured during a full year of 2017-2018. We used such ultraviolet values which are measured at the same hour of the day to satisfy the same symmetry criteria which are necessary in random matrix theory. These data are unfolded and classified in different sequences to analyze in the nearest neighbor spacing distribution framework via the maximum likelihood estimation technique. Results: Strong correlation is yielded for daily values of UVA in comparison with the other types of ultraviolet radiations. Also, we considered the dependence of correlation degrees of these three types of ultraviolet to average temperature and humidity at different months. Conclusion: The results propose more correlation of UVA indices in August while such correlation of UVC radiations are yielded in December.
Author Seidi, Masoud
Asadpour, Nikan
Sabri, Hadi
Malekzadeh, Reza
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Snippet Purpose: The correlation of different samples can be described by analytical models such as random matrix theory. In this study, we tried to describe the...
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SubjectTerms Environmental Radiation
Modeling
Random Matrix Theory
Ultra Violet
Title Prediction of Solar Ultraviolet Radiations Using Random Matrix Theory
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