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| 机器学习在地震观测数据异常提取中的应用 |
| Application of Machine Learning to Anomaly Extraction from Seismic Observation Data |
| 投稿时间：2023-11-27 修订日期：2024-02-27 |
| DOI： |
| 中文关键词: 地震观测 应变观测 异常提取 机器学习 |
| 英文关键词: seismic observation strain observation anomaly extraction machine learning |
| 基金项目:海南省自然科学基金高层次人才项目( 622RC669,322RC659) |
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| 中文摘要: |
| 本文参考了近年来国内外对于地震观测方法和地震数据异常提取的相关文献，对当前地震观测和地震数据异常提取领域涉及到的方法和技术进行概述。首先按照应变观测、电离层观测、流体观测、电磁观测和其他的观测方式对不同的地震观测方法和结论进行叙述；接下来对机器学习在地震数据异常提取的应用场景进行分析，对目前使用较多的机器学习方法进行分析和概述；最后，对地震观测方法和地震数据异常提取进行总结，对地震预测的发展趋势进行展望。 |
| 英文摘要: |
| In this paper, we refer to the relevant literature on seismic observation methods and seismic data anomaly extraction at home and abroad in recent years, and provide an overview of the current methods and technologies involved in the field of seismic observation and seismic data anomaly extraction. Firstly, different seismic observation methods and conclusions are described according to strain observation, ionospheric observation, fluid observation, electromagnetic observation and other observation methods. Next, the application scenarios of machine learning in seismic data anomaly extraction are analyzed, and the more used machine learning methods are analyzed and outlined. Finally, the seismic observation methods and seismic data anomaly extraction are summarized, and the seismic forecasting development trend is outlooked. |
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