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Updated: Sep 19, 2025

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用生成模型对地质物理流体动力学的贝叶斯推理
Alexander Lobbe1, Dan Crisan1, Oana Lang2
1Imperial College London, London, UK.
概括
本研究介绍了用于校准复杂数值模型的扩散生成模型. 这些模型创建合成数据,提高颗粒过器的准确性,以实现高效的数据同化和模型缩小.
科学领域:
- 计算数学 计算数学 计算数学
- 科学计算科学计算
- 数据同化数据同化
背景情况:
- 数据同化对于通过整合现实世界观测来提高数值模型准确性至关重要.
- 校准高维,非线性系统带来了重大的计算挑战.
研究的目的:
- 为复杂系统使用扩散生成模型提出一种新的校准方法.
- 在高维系统中展示高效的模型缩小和数据同化.
主要方法:
- 利用扩散生成模型来产生与数值解决方案一致的合成数据.
- 将这些合成样本应用于高分辨率旋转浅水方程的模型缩小.
- 将样品集成到增强的颗粒过方法中,采用和震动.
主要成果:
- 生成模型有效地产生了用于校准复杂系统的合成数据.
- 从一个高维系统 (自由度10^4) 到一个减少的随机系统,实现了高效的数据同化.
- 证明了提高颗粒过器的准确性和计算效率.
结论:
- 扩散生成模型为数据同化和模型校准提供了计算效率高的解决方案.
- 拟议的方法提高了数值模拟的准确性和预测能力.
- 这种方法代表了在生成模型和贝叶斯推理中的反向问题的重大进步.
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