Limiting conditions prediction using machine learning for loss of condenser vacuum event-Reference-Cited by-同舟云学术

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Limiting conditions prediction using machine learning for loss of condenser vacuum event

Published:2023-12 Issue:12 Volume:55 Page:4607-4616
ISSN:1738-5733
Container-title:Nuclear Engineering and Technology
language:en
Short-container-title:Nuclear Engineering and Technology

Author:

Shin Dong-Hun,Park Moon-Ghu^ORCID,Jeong Hae-Yong,Lee Jae-Yong,Sohn Jung-Uk,Kim Do-Yeon

Funder

Ministry of Trade, Industry and Energy

Korea Institute of Energy Technology Evaluation and Planning

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering

Reference32 articles.

1. Safety Margins of Operating Reactors-Analysis of Uncertainties and Implications for Decision Making;Agency,2003

2. Deterministic Safety Analysis for Nuclear Power Plants : Specific Safety Guide;International Atomic Energy,2019

3. TR-KHNP-0009,2007

4. Classes of kernels for machine learning: a statistics perspective;Genton;J. Mach. Learn. Res.,2002

5. Data mining: machine learning, statistics, and databases;Mannila,1996

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A hybrid model based on complementary ensemble empirical mode decomposition, sample entropy and long short-term memory neural network for the prediction of time series signals in NPPs;Progress in Nuclear Energy;2024-11

2. Application of artificial neural network for assembly homogenized equivalence parameter generation;Progress in Nuclear Energy;2024-08

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