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Updated: May 9, 2025

Using Generative Art to Convey Past and Future Climate Transitions
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基于机器学习的南中国海人为I的预测

Jinxiao Hou1, Tong Zhang2, Yanyun Wang3

  • 1Xi'an Accelerator Mass Spectrometry Center, State Key Laboratory of Loess Science, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China.

Journal of environmental radioactivity
|May 3, 2025
PubMed
概括

机器学习模型预测了放射性-129 (129I) 在海洋环境中的分散. 盐度,温度和水深显著影响129I水平,有助于放射性风险评估.

关键词:
(129) 一个I.分散和预测和预测.机器学习是机器学习.核污染 核污染 核污染

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