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Updated: May 29, 2025

Laser-heating and Radiance Spectrometry for the Study of Nuclear Materials in Conditions Simulating a Nuclear Power Plant Accident
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Published on: December 14, 2017

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源代码是核事故的反转,随机释放的持续时间基于机器学习

Wendong Yang1, Yifei Wu1, Wenbao Jia1

  • 1Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Journal of hazardous materials
|February 4, 2025
PubMed
概括

一个使用长期短期记忆 (LSTM) 神经网络的新机器学习模型准确地估计了核事故期间放射性核素释放率和持续时间. 这种先进的源代码术语反转方法减少了对先前数据的依赖,提高了应急响应能力.

关键词:
这是LSTM的LSTM.核事故 核事故 核事故源头术语反向的反转.

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