在高信息内容数据和多参数模型的跨维贝叶斯地声逆转中进行并行化
1School of Earth and Ocean Sciences, University of Victoria, Victoria, British Columbia V8W 2Y2, Canadasdosso@uvic.ca.
跨维贝叶斯反转通过概率取样层数和参数来改进海底地球声学建模. 并行炼增强了这种方法,用于具有高度信息性的数据的复杂问题.
科学领域:
- 海洋声学 海洋声学
- 地质物理的反转.
- 贝叶斯的推理 贝叶斯的推理
背景情况:
- 跨维 (跨D) 贝叶斯反转是海底地球声学模型估计的关键.
- 它结合了模型选择和不确定性量化.
- 当数据具有高度信息性或模型复杂时,就会出现挑战,从而降低了改变维度的接受概率.
研究的目的:
- 为了研究跨D贝叶斯反转平行炼的有效性.
- 为解决具有挑战性的反向问题的维度变化接受的局限性.
主要方法:
- 使用并行炼,这是一种涉及多个相互作用的马尔科夫链的技术,可能性不同.
- 将这一点应用于地声学模型估计的跨-D贝叶斯反转.
主要成果:
- 并行炼可以提高跨-D反转中维度变化的接受率.
- 这使得海底地球声学模型的估计更加有效和稳健,即使使用复杂的数据.
结论:
- 并行化是一种有效的策略,以克服跨D贝叶斯反转中的收问题.
- 这一进步使得从海洋声学数据中更准确地进行海底地声学表征.
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