Monitoring of the Efficiency of the IRT-T Reactor Heat Exchanger System by Machine Learning Method

This paper presents a study aimed at studying and evaluating the possibility of using machine learning in methods of predictive analysis of the operation of the cooling system of the IRT-T reactor. Machine learning is a subspecies of artificial intelligence used in large-volume data analytics. The currently existing methods of processing data on technological parameters are imperfect and do not allow predicting the development of operational events. The proposed approach will allow not only to centrally collect data on technological parameters, but also to output an analysis of possible outcomes and recommendations for changing operating modes.