Journal
MEASUREMENT
Volume 51, Issue -, Pages 34-41Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2014.01.030
Keywords
Artificial neural network; Gamma-ray attenuation; MCNP; Multiphase flow-prediction
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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%. (C) 2014 Elsevier Ltd. All rights reserved.
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