用于地震参数估算的两种贝叶斯概率算法分析

李拴虎, 高立新, 丁风和, 陈立峰, 杨红樱

李拴虎, 高立新, 丁风和, 陈立峰, 杨红樱. 2016: 用于地震参数估算的两种贝叶斯概率算法分析. 地震学报, 38(6): 952-955. DOI: 10.11939/jass.2016.06.015
引用本文: 李拴虎, 高立新, 丁风和, 陈立峰, 杨红樱. 2016: 用于地震参数估算的两种贝叶斯概率算法分析. 地震学报, 38(6): 952-955. DOI: 10.11939/jass.2016.06.015
Li Shuanhu, Gao Lixin, Ding Fenghe, Chen Lifeng, Yang Hongying. 2016: Application of two Bayesian probability algorithms to the estimation of earthquake parameters. Acta Seismologica Sinica, 38(6): 952-955. DOI: 10.11939/jass.2016.06.015
Citation: Li Shuanhu, Gao Lixin, Ding Fenghe, Chen Lifeng, Yang Hongying. 2016: Application of two Bayesian probability algorithms to the estimation of earthquake parameters. Acta Seismologica Sinica, 38(6): 952-955. DOI: 10.11939/jass.2016.06.015

用于地震参数估算的两种贝叶斯概率算法分析

基金项目: 

内蒙古自治区地震局局长基金课题 2016YC01

内蒙古自治区地震局局长基金课题(2016YC01)资助

详细信息
    通讯作者:

    李拴虎, e-mail: lizhengke06@126.com

  • 中图分类号: P315.08

Application of two Bayesian probability algorithms to the estimation of earthquake parameters

  • 图  1   研究区的实际震源(a)与理论震源(b)的分布特征

    Figure  1.   Distribution of actual epicenters (a) and the theoretical epicenters (b) in the studied area

    图  2   先验概率、似然概率和贝叶斯概率的计算值比较

    Figure  2.   Comparison of the calculated values of the prior probability (squares), likelihood probability (circles) and Beyesian probability (triangles)

    图  3   各区块内ML≥6.0地震事件的分布(a)和贝叶斯算法平滑之后得到的发震概率(b)

    Figure  3.   Distribution of earthquake events with ML≥6.0 in subregions (a) and the rate estimates for ML≥6.0 earthquakes after the Bayesian smoothing (b)

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出版历程
  • 收稿日期:  2016-03-21
  • 修回日期:  2016-06-12
  • 发布日期:  2016-10-31

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