Supervised machine learning with regression for the IRT-T reactor cooling system
Maxim Kublinskiy,
Nikita Smolnikov,
Artem Naymushin
Abstract:The purpose of this study is to create a machine learning model for the IRT-T reactor cooling system, which can estimate and predict the temperature difference in the secondary circuit. To do this, data was downloaded from the SCADA system, then an application was developed for converting and preprocessing this data. Then regression and classification models were constructed that evaluated the efficiency of the cooling system and its ability to predict changes in the temperature drop on heat exchangers. The ma… Show more
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