(2024) Prediction of Solar Ultraviolet Radiations Using Random Matrix Theory. Frontiers in Biomedical Technologies. pp. 6-13. ISSN 23455829 (ISSN)
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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. © 2024 Tehran University of Medical Sciences.
Item Type: | Article |
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Keywords: | Environmental Radiation Modeling Random Matrix Theory Ultra Violet Article humidity maximum likelihood method prediction solar radiation sun sunburn temperature ultraviolet A radiation ultraviolet B radiation ultraviolet C radiation ultraviolet radiation urban area |
Page Range: | pp. 6-13 |
Journal or Publication Title: | Frontiers in Biomedical Technologies |
Journal Index: | Scopus |
Volume: | 11 |
Number: | 1 |
Identification Number: | https://doi.org/10.18502/fbt.v11i1.14505 |
ISSN: | 23455829 (ISSN) |
Depositing User: | خانم ناهید ضیائی |
URI: | http://eprints.mui.ac.ir/id/eprint/30499 |
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