使用神经网络在富含莫纳的沿海环境中建模马辐射强度
Miriam Mathias Gigi1, Marcos Tadeu D'Azeredo Orlando2, Jacyra Soares1
1University of São Paulo, Institute of Astronomy, Geophysics and Atmospheric Sciences, Department of Atmospheric Sciences, Rua do Matão, 1226, Cidade Universitária, São Paulo, SP, 05508-090, Brazil.
Journal of environmental radioactivity
|March 5, 2026
概括
梅伊佩海的高背景辐射受到的 (220Rn) 的影响. 一个预测模型显示,高度和温度在这个热带环境中显著影响了玛辐射水平.
科学领域:
- 环境科学 环境科学
- 放射学科学 放射学科学
- 地质物理学 地质物理学
背景情况:
- 巴西的Meaipe海由于含的莫纳砂而呈现出高水平的自然背景辐射.
- 的衰变释放了 (220Rn),导致环境放射性.
- 该地区的潜在健康影响需要环境放射性研究.
研究的目的:
- 分析玛辐射强度及其与气象和土壤变量之间的相关性.
- 调查与多伦呼气相关的辐射的时间和垂直变化.
- 为每小时的马辐射开发一个预测模型.
主要方法:
- 连续测量玛辐射强度的现场测量.
- 使用2018-2022年的数据开发一个多层感知子模型.
- 模型优化使用阿达德尔塔算法与ReLU激活和分析变量影响.
主要成果:
- 多层感知子模型在预测马辐射方面实现了高精度 (R2 = 0.99).
- 重要变量:高度 (41%),表面长波辐射 (12%) 和一年中的一天 (9%).
- 空气和土壤温度上升10°C与玛辐射强度上升18%有关.
结论:
- 该模型准确地捕获了马辐射模式,受表面辐射和温度的影响.
- 高度和气象因素是马辐射变化的关键驱动因素.
- 这些发现增强了对热带沿海环境中的辐射动态的理解.
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