Prediction of Radiation Shielding Thickness of Concretes by Artificial Neural Networks and Multiple Regression Methods

In this study, concretes for using in radiation shielding thickness was determined in different energy ranges using tenth value layer by artificial neural networks (ann) and multiple regression methods. radiation energy values, tenth value layers (tvl) and negatif logoritmic of transmission percent (n) were selected as input parameres and concrete shielding thickness values selected as output parameters consequently, developed artificial neural networks and multiple regression models outputs were compared with theoretical results and it was seen that the results were harmonious.