Summary
This paper presents an Artificial Neural Network (ANN) model for determining the total radioactivity in Hazar Lake (Sivrice, Turkey). In order to cope with complex calculations and experiments required for the determination of total radioctivity. The proposed ANN system employs the individual training strategy with fixed-weight and supervised models. The simulation demonstrate the feasibility of the neural based model. Compared to the classical methods, the proposed ANN-based model makes the processes much easier.
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Kulahci, F., Özer, A. & Do?ru, M. Prediction of the radioactivity in Hazar Lake (Sivrice, Turkey) by artificial neural networks. J Radioanal Nucl Chem 269, 63–68 (2006). https://doi.org/10.1007/s10967-006-0230-6
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DOI: https://doi.org/10.1007/s10967-006-0230-6