Monitoring of the Efficiency of the IRT-T Reactor Heat Exchanger System by Machine Learning Method; Physics of Particles and Nuclei Letters; Vol. 21, iss. 4

Monitoring of the Efficiency of the IRT-T Reactor Heat Exchanger System by Machine Learning Method; Physics of Particles and Nuclei Letters; Vol. 21, iss. 4

Detalles Bibliográficos
Parent link:Physics of Particles and Nuclei Letters=Письма в журнал «Физика элементарных частиц и атомного ядра». Письма в ЭЧАЯ.— .— New York: Springer Science+Business Media LLC.
Vol. 21, iss. 4.— 2024.— P. 808-810
Autor Principal: Kublinsky M. K. Maksym Konstantinovich
Autor Corporativo: National Research Tomsk Polytechnic University (570)
Outros autores: Smolnikov N. V. Nikita Viktorovich, Naymushin A. G. Artem Georgievich
Summary:Title screen
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.
Текстовый файл
AM_Agreement
Idioma:inglés
Publicado: 2024
Subjects:
research reactor
cooling system
heat exchangers
data analytics
artificial intelligence
machine learning
электронный ресурс
труды учёных ТПУ
Acceso en liña:https://doi.org/10.1134/S1547477124701413
Статья на русском языке
Formato: Electrónico Capítulo de libro
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=675047

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