Prediction Primary Radiation Shielding Wall Thickness with Artificial Neural Networks
ACTA PHYSICA POLONICA A, cilt.123, sa.2, ss.171-172, 2013 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 123 Sayı: 2
- Basım Tarihi: 2013
- Doi Numarası: 10.12693/aphyspola.123.171
- Dergi Adı: ACTA PHYSICA POLONICA A
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.171-172
- Süleyman Demirel Üniversitesi Adresli: Evet
Özet
In this study, wall thickness for using in primary radiation shielding was determined in different energy ranges using tenth value layer by artificial neural networks. Radiation energy values, tenth value layers and negative logarithm of transmission factor (n) were selected as input parameters and wall shielding thickness values selected as output parameters. Consequently, developed artificial neural networks model outputs were compared with experimental results and it was seen that the results were harmonious. DOI: 10.12693/APhysPolA.123.171