A comparative study on applicability and efficiency of machine learning algorithms for modeling gamma-ray shielding behaviors
The mass attenuation coefficient is the primary physical parameter to model narrow beam gamma-ray attenuation. A new machine learning based approach is proposed to model gamma-ray shielding behavior of composites alternative to theoretical calculations. Two fuzzy logic algorithms and a neural networ...
Main Authors: | Bayram Bilmez, Ozan Toker, Selçuk Alp, Ersoy Öz, Orhan İçelli |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-01-01
|
Series: | Nuclear Engineering and Technology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S173857332100454X |
Similar Items
-
Study of Gamma-ray Shielding of Two Different Heavy Metals and their Combination for Cs-137 and Co-60 Sources
by: Mohamed E. M. Eisa, et al.
Published: (2023-02-01) -
Enhancement of Bentonite Materials with Cement for Gamma-Ray Shielding Capability
by: Ahmed M. El-Khatib, et al.
Published: (2021-08-01) -
Calculation and Study of Gamma ray Attenuation Coefficients for Different Composites
by: K.H. Mahdi, et al.
Published: (2017-05-01) -
Investigation of Gamma-Ray Shielding Properties of Bismuth Oxide Nanoparticles with a Bentonite–Gypsum Matrix
by: Mahmoud I. Abbas, et al.
Published: (2023-03-01) -
Experimental Study on The Gamma Ray Absorption Properties of Lanthanum and Cerium Borides
by: Esra Kurt, et al.
Published: (2023-11-01)