自发育的人工智能框架更好地解读短期的大地震.
1CCEE Department, Iowa State University, Ames, IA, 50011, USA. icho@iastate.edu.
Scientific reports
|September 20, 2024
概括
一个新的人工智能 (AI) 框架将地震数据转化为机器学习 (ML) 的功能,可以提前几周预测大地震. 这种自我进化的系统增强了地震预测能力.
科学领域:
- 地质物理学 地质物理学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 由于数据限制和复杂的物理,预测大型地震 (EQ) 仍然具有挑战性.
- 传统和当前的机器学习 (ML) 方法与地震预测作斗争.
研究的目的:
- 开发一种新型的人工智能 (AI) 框架,用于将原始地震数据转化为ML友好的功能.
- 为了实现人工智能模型的自我进化,以改善大型EQs的短期预测.
主要方法:
- 利用基础物理和数学将观测地震数据转换为新的特征.
- 实现一个先进的强化学习 (RL) 架构,用于自我发展的人工智能模型.
- 整合透明的ML模型来预测大EQ (≥6.5) 的大小和空间位置.
主要成果:
- 人工智能框架成功地将原始EQ数据转化为可用的ML功能.
- 透明的ML模型重现了大EQ发生前几周的大小和空间位置.
- 使用40年的美国西部地震数据进行验证,与现有方法相比显示出有希望的结果.
结论:
- 开发的AI框架为大地震研究提供了一种新的方法.
- 这种人工智能技术可以建立一个新的地震特征数据库,以实现持续的自我进化.
- 该系统显示了改善短期地震预测的潜力.
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