Artificial neural network (ANN) is an appropriate method used to handle the modeling,
prediction and classification problems. In this study, based on nuclear technique in annular
multiphase regime using only one detector and a dual energy gamma-ray source, a proposed
ANN architecture is used to predict the oil, water and air percentage, precisely. A
multi-layer perceptron (MLP) neural network is used to develop the ANN model in MATLAB
7.0.4 software. In this work, number of detectors and ANN input features were reduced to
one and two, respectively. The input parameters of ANN are first and second full energy
peaks of the detector output signal, and the outputs are oil and water percentage. The
obtained results show that the proposed ANN model has achieved good agreement with
the simulation data with a negligible error between the estimated and simulated values.
Defined MAE% error was obtained less than 1%.
