Abstract
The pattern recognition methodologies and artificial neural networks were used widely for the IBR-2M pulsed reactor noise diagnostics. The cluster analysis allows a detailed study of the structure and fast reactivity effects of IBR-2M and nonlinear autoregressive neural network (NAR) with local feedback connection allows predicting slow reactivity effects. In this work we present results of a study on pulse energy noise dynamics and prediction of liquid sodium flow rate through the core of the IBR-2M reactor using cluster analysis and an artificial neural network.
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Pepelyshev, Y.N., Tsogtsaikhan, T. & Ososkov, G.A. Application of cluster analysis and autoregressive neural networks for the noise diagnostics of the IBR-2M reactor. Phys. Part. Nuclei Lett. 13, 704–707 (2016). https://doi.org/10.1134/S1547477116050381
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DOI: https://doi.org/10.1134/S1547477116050381