• ISSN 2097-1893
  • CN 10-1855/P

机器学习在地震学中的应用进展

杨旭 李永华 盖增喜

引用本文: 杨旭,李永华,盖增喜. 机器学习在地震学中的应用进展. 地球与行星物理论评,2021,52(1):76-88
Yang X, Li Y H, Ge Z X. Machine learning and its application in seismology. Reviews of Geophysics and Planetary Physics, 2021, 52(1):76-88

机器学习在地震学中的应用进展

doi: 10.19975/j.dqyxx.2020-006
基金项目: 中国地震局地球物理研究所基本业务专项资助项目(DQJB19A0111);国家自然科学基金资助项目(U1839210, 41874108)
详细信息
    通讯作者:

    杨旭(1991-),女,博士研究生,主要从事地震到时拾取与地震定位方面的研究. E-mail: yangxu161@cea-igp.ac.cn

  • 中图分类号: P315.0

Machine learning and its application in seismology

Funds: Supported by the Basal Research Fund of Institute of Geophysics, China Earthquake Administration (DQJB19A0111) and the National Science Foundation of China (No.U1839210, 41874108)
  • 摘要: 理解并预测多尺度、高维度和非线性的地震学现象是一个极具挑战性的科学任务. 与日俱增的海量观测数据降低了信息收集和信息解读之间的耦合程度,增加了信息解读的抽象性和不确定性. 然而,伴随大数据一同来临的还有人工智能计算机技术——机器学习. 机器学习突出的隐式关系提取和复杂任务处理能力推动着研究学者们不断将机器学习的应用推向更广阔的领域. 本文介绍了地震学中常用的机器学习算法及其应用范围,讨论了人工智能与地震数据相结合的发展方向.

     

  • 图  1  机器学习在地震学领域中的科技文章年度数量统计图(Scopus数据库)

    Figure  1.  Yearly number of scientific papers on topic of machine learning in seismology (Scopus Database)

    图  2  常用的机器学习算法类型

    Figure  2.  Types of commonly used machine learning algorithms

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出版历程
  • 收稿日期:  2020-07-03
  • 录用日期:  2020-08-14
  • 网络出版日期:  2021-09-13
  • 刊出日期:  2021-01-01

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