机器学习在地震事件自动分类中的应用
Machine Learning Applied in Auto-classify of Seismic Events
刘甜甜 1王禄军 1张晖1
作者信息
- 1. 内蒙古自治区地震局,呼和浩特 010051
- 折叠
摘要
使用地震事件分类识别软件(SERS)对内蒙古地震台网 2019-2022 年编报的内蒙古东部地区 20 次分类存疑的地震事件进行类型识别,模型识别率为 90.4%;通过对比其与人工编目结果发现,只有 3 次事件识别为天然地震,概率较低.对这 3 次地震事件记录数据的振幅比和时频分析结果表明,震中距较近台站的波形记录具有明显的P波振幅大、能量高的特点,结合研究内蒙古东部地区地质构造及场地响应的相关文献,推测这些地震事件分类识别主要受场地影响,存在场地放大效应.
Abstract
In this paper,SERS(Seismic Event Recognition System)was used to classify 20 seismic events with doubtful classification in the east of Inner Mongolia cataloged by Inner Mongolia Regional Seismological Network from 2019 to 2022.Recognition rate of the model was 90.4%.Comparing with manual catalog,only 3 events were recognized as natural earthquakes,with lower probability.According to the results of amplitude-ratio and time-frequency analysis of these events,P waves of the stations close to the epicentre have evident characteristics of blast events,such as high-amplitude and high-energy.And combined with relative documents studying the geological formation and site response,the paper speculates that the classification of seismic events is mainly site-influenced.
关键词
机器学习/地震事件自动分类/SERS/场地放大效应Key words
machine learning/auto-classify of seismic events/SERS/site amplification effect引用本文复制引用
基金项目
内蒙古自治区地震局局长基金(2022JC11)
内蒙古自治区地震局局长基金(2023MS06)
出版年
2024
NETL
NSTL
万方数据