Monitoring of the Efficiency of the IRT-T Reactor Heat Exchanger System by Machine Learning Method
IF 0.4
Q4 PHYSICS, PARTICLES & FIELDS
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.
用机器学习方法监测 IRT-T 反应堆热交换器系统的效率
摘要 本文介绍了一项研究，旨在研究和评估在 IRT-T 反应堆冷却系统运行预测分析方法中使用机器学习的可能性。机器学习是大量数据分析中使用的人工智能的一个分支。目前现有的技术参数数据处理方法并不完善，无法预测运行事件的发展。拟议的方法不仅可以集中收集技术参数数据，还可以输出对可能结果的分析和改变运行模式的建议。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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来源期刊
Physics of Particles and Nuclei Letters
PHYSICS, PARTICLES & FIELDS-
CiteScore
0.80
自引率
20.00%
发文量
108
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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