{"title":"Monitoring of the Efficiency of the IRT-T Reactor Heat Exchanger System by Machine Learning Method","authors":"M. Kublinskiy, N. Smolinkov, A. Naimushin","doi":"10.1134/s1547477124701413","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>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.</p>","PeriodicalId":730,"journal":{"name":"Physics of Particles and Nuclei Letters","volume":"36 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics of Particles and Nuclei Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1134/s1547477124701413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, PARTICLES & FIELDS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍：
The journal Physics of Particles and Nuclei Letters, brief name Particles and Nuclei Letters, publishes the articles with results of the original theoretical, experimental, scientific-technical, methodological and applied research. Subject matter of articles covers: theoretical physics, elementary particle physics, relativistic nuclear physics, nuclear physics and related problems in other branches of physics, neutron physics, condensed matter physics, physics and engineering at low temperatures, physics and engineering of accelerators, physical experimental instruments and methods, physical computation experiments, applied research in these branches of physics and radiology, ecology and nuclear medicine.
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