Application of cluster analysis and autoregressive neural networks for the noise diagnostics of the IBR-2M reactor
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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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