|本期目录/Table of Contents|

[1]邵磊,王长在.机器学习的密度聚类算法在地震活动性研究中的应用[J].地震研究,2025,(03):361-369.[doi:10.20015/j.cnki.ISSN1000-0666.2025.0038 ]
 SHAO Lei,WANG Changzai.Application of the Density Clustering Algorithm in Machine Learning to Seismic Activity[J].Journal of Seismological Research,2025,(03):361-369.[doi:10.20015/j.cnki.ISSN1000-0666.2025.0038 ]
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机器学习的密度聚类算法在地震活动性研究中的应用(PDF/HTML)

《地震研究》[ISSN:1000-0666/CN:53-1062/P]

卷:
期数:
2025年03期
页码:
361-369
栏目:
出版日期:
2025-04-15

文章信息/Info

Title:
Application of the Density Clustering Algorithm in Machine Learning to Seismic Activity
作者:
邵磊1王长在2
(1.湖南省地震局,湖南 长沙 410004; 2.中国地震局地球物理研究所,北京 100081)
Author(s):
SHAO Lei1WANG Changzai2
(1.Hunan Earthquake Agency,Changsha 410004,Hunan,China)(2.Institute of Geophysics,China Earthquake Administration,Beijing 100081,China)
关键词:
机器学习 DBSCAN算法 地震活动性 地震精定位
Keywords:
machine learning the DBSCAN algorithm seismic activity precise earthquake location
分类号:
P315.5
DOI:
10.20015/j.cnki.ISSN1000-0666.2025.0038
摘要:
针对大范围的地震活动密集区精定位实施中有效划分子区域问题,通过多次模拟数据实验,检验机器学习的各种聚类算法后,得出基于密度聚类的DBSCAN算法最适用于断层或地震丛集的地震聚类。使用DBSCAN算法对川滇地区共322 070个M1.2~5.1地震事件进行了聚类,共得到9个明显地震簇,对其中的鲜水河断裂带南段和安宁河断裂带北段交会区域的地震簇以及鲜水河—安宁河断裂带西北部区域的2014年康定MS6.3地震序列地震簇,使用双差地震定位方法进行了精定位,并分析了地震空间分布特征。结果表明:鲜水河断裂带南段和安宁河断裂带北段交会区域的地震密集地分布在断裂周围,走向与断裂走向基本一致,纵剖面揭示了该断裂在深部以西倾为主要特征; 康定地震序列具有与走滑断裂地震分布一致的特征,断层在深部倾角几乎垂直。进一步研究了2009年1月—2021年3月鲜水河断裂带南段与安宁河断裂带北段交会区域b值空间分布特征,揭示了2022年9月5日泸定MS6.8地震的发震位置处于明显的低b值区域。
Abstract:
Aiming at the problem of effectively sub-dividing sub-regions for precise earthquake location in large-scale areas with intensive seismic activity,this paper,through multiple simulated data experiments and evaluations of various clustering algorithms in machine learning,concludes that the DBSCAN algorithm is most suitable for earthquake clustering in faults or earthquake swarms.Based on this,seismic activity studies are conducted to analyze and reveal spatial differences in the relative levels of current tectonic stress accumulation along fault zones,serving as an important foundation for analyzing the current activity patterns of faults(segments)and potential strong earthquake hazard zones.The DBSCAN algorithm was applied to cluster a total of 322 070 earthquake events in Sichuan-Yunnan region,resulting in nine distinct earthquake clusters.Among them,precise locations are determined using the double-difference earthquake location algorithm for the earthquake cluster in the intersection area of the southern segment of the Xianshuihe fault zone and the northern segment of the Anninghe fault zone,as well as for the Kangding MS6.3 earthquake sequence to the northwest,and the spatial distribution characteristics of earthquakes are also analyzed.The relocated results show that the Kangding earthquake sequence exhibits features consistent with the earthquake distribution on the strike-slip fault.The fault has an almost vertical dip angle.Earthquakes in the intersection area of the southern segment of the Xianshuihe fault zone and in the northern segment of the Anninghe fault zone are also densely distributed around the faults,with orientations generally consistent with the fault strikes.The longitudinal profile reveals the deep structural features of the fault.Furthermore,this paper investigates the spatial distribution characteristics of the b-value in the southern segment of the Xianshuihe fault zone and in the northern segment of the Anninghe fault zone from January 2009 to March 2021,revealing that the location of the Luding MS6.8 earthquake that occurred on September 5,2022 is in the area where b-value is obviously low.

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备注/Memo

备注/Memo:
收稿日期:2024-11-25.
基金项目:国家重点研发计划(2021YFC3000600,2021YFC3000702); 中国地震局地球物理研究所基本科研业务专项(DQJB24Z12).
第一作者简介:邵 磊(1984-),高级工程师,主要从事地震重新定位、地震活动性及地震安全性评价等工作.E-mail:79541207@qq.com.
通信作者简介:王长在(1982-),副研究员,博士,主要从事地震震源区速度结构及地震精定位研究.E-mail:wangchangzai@cea-igp.ac.cn.
更新日期/Last Update: 2025-04-15