An Adaptive Neuro-Fuzzy Inference System (ANFIS) of Radioactivity Levels in Hazar Lake

Abstract

In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model is proposed for thedetermination of alpha radioactivity of Hazar Lake waters and for the prediction of its unknown values. Themodel parameters of the lake water are pH, total hardness (TH), depth, electrical conductivity (EC), and alpharadioactivity. ANFIS model is performed using the back-propagation algorithm, which has the five layers.Average relative error between measurements predicted by theoretical (ANFIS) and experimental data isapproximately 0.7043%. The relative error between the test data and the radioactivity data change between0.06% and 14%. Additionally, validity of the model is also tested with a regression model. The predictedresults with the ANFIS model is better as statistically than the regression model.