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DEEP NEURAL NETWORKS AS A TOOL TO ESTIMATION OF COSMIC RADIATION DOSE RECEIVED ON FLIGHT

Date
2022
Author
Erol, Aydin
EMİRHAN, Mehmet Erhan
AKKUŞ, Baki
GÜDEKLİ, Ertan
Inci, Cisem Ilayda
YILMAZ, Ayberk
YILMAZ ALAN, HATİCE
FAYDASIÇOK, Özlem
Susam, Lidya Amon
Samli, Ruya
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Abstract
Cosmic radiation is an ionizing radiation produced when primary protons and a particles from outside the solar system interact with components of the earth's atmosphere. Cosmic radiation is a general term for radiation produced by high-energy subatomic particles from outer space and, more importantly, secondary (ionizing) radiation from the sun and high-energy subatomic particles that react with nitrogen, oxygen, and other elements in the atmosphere. In this study, Deep Neural Networks (DNNs) via Multilayer Perceptrons (MLPs) were used to estimate the radiation doses due to cosmic radiation for different domestic flights related with Istanbul and Ankara Airports in Turkey. Dose values were calculated with the CARI-7A program and DNNs. The parameters for calculating dose rates are latitude, longitude and depth. The results obtained compared and discussed.
URI
http://hdl.handle.net/20.500.12627/183426
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İstanbul Üniversitesi Akademik Arşiv Sistemi (ilgili içerikte aksi belirtilmediği sürece) Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.

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Creative Commons Lisansı

İstanbul Üniversitesi Akademik Arşiv Sistemi (ilgili içerikte aksi belirtilmediği sürece) Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.

DSpace software copyright © 2002-2016  DuraSpace
Contact Us | Send Feedback
Theme by 
Atmire NV