An Artificial Neural Network-Based Estimation of Bremsstarahlung Photon Flux Calculated by MCNPX

• Authors: H. Tekin , T. Manici , E. Altunsoy , K. Yilancioglu , B. Yilmaz
• Languages of publication: EN

Abstracts

EN

Bremsstrahlung has an important place in the field of experimental physics, especially for description of photon-matter interaction and for characterization and analysis of materials. Bremsstrahlung photon is created by a high-energy electron, deflected in the electric field of atomic nucleus. Bremsstrahlung is also important for experimental studies, not only in the field of nuclear physics and particle physics but also in the fields of solid state physics, applied physics and astrophysics. In recent years, Monte Carlo simulation has become a widely used method for calculations related to bremsstrahlung. On the other hand, predictions by using artificial neural network can be performed with high accuracy. This study aims at observing variation in the photon flux as unction of target thickness and at processing output data by using an artificial neural network. We achieved a high degree of compatibility between two different methods. This study suggests that artificial neural network is a powerful tool for prediction of Bremsstrahlung and for other scientific problems.

Keywords

EN

07.05.Mh; 23.20.Nx; 87.10.R

Discipline

• 07.05.Mh: Neural networks, fuzzy logic, artificial intelligence
• 23.20.Nx: Internal conversion and extranuclear effects (including Auger electrons and internal bremsstrahlung)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2017
• Volume: 132
• Issue: 3
• Pages: 967-969

Dates

published

2017-09

Contributors

author

H. Tekin

• Uskudar University, Vocational School of Health Services, Radiotherapy Department, İstanbul, Turkey
• Usküdar University, Medical Radiation Research Center (USMERA), İstanbul, Turkey

author

T. Manici

• Usküdar University, Medical Radiation Research Center (USMERA), İstanbul, Turkey

author

E. Altunsoy

• Usküdar University, Medical Radiation Research Center (USMERA), İstanbul, Turkey
• Uskudar University, Vocational School of Health Service, Medical Imaging Department, Istanbul, Turkey

author

K. Yilancioglu

• Uskudar University, Faculty of Engineering and Natural Sciences, Molecular Biology and Genetics Department, İstanbul, Turkey

author

B. Yilmaz

• Okan University, Faculity of Medicine, Department of Radiology, Istanbul, Turkey

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Identifiers

DOI

10.12693/APhysPolA.132.967