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

YILMAZ A., YILMAZ ALAN H., FAYDASIÇOK Ö., Susam L. A., Samli R., AKKUŞ B., ...More

UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN-SERIES A-APPLIED MATHEMATICS AND PHYSICS, vol.84, no.2, pp.187-202, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 84 Issue: 2
  • Publication Date: 2022
  • Journal Name: UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN-SERIES A-APPLIED MATHEMATICS AND PHYSICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.187-202
  • Keywords: aircrew, cosmic radiation, flight, machine learning, deep learning, multilayer perceptrons, CREW DOSIMETRY, AIRCRAFT, EXPOSURE, ALTITUDES, MODEL
  • Istanbul University Affiliated: Yes

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.