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地震

地震 ›› 2011, Vol. 31 ›› Issue (2): 114-121.

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基于贝叶斯判别分析的地震应急响应等级初判方法

刘在涛, 王栋梁, 张维佳, 冯蔚, 郑通彦   

  1. 中国地震台网中心, 北京 100045
  • 收稿日期:2010-10-21 修回日期:2011-01-10 出版日期:2011-04-30 发布日期:2021-09-09
  • 作者简介:刘在涛(1977-), 男, 山东章丘人, 高级工程师, 2005年获硕士学位, 主要从事地震灾害应急及指挥系统建设等研究。
  • 基金资助:
    中国地震局地震应急青年课题(CEAEDEM-201020)资助

Early Judgment Method of Earthquake Emergency Response Level Based on Bayesian Classification

LIU Zai-tao, WANG Dong-liang, ZHANG Wei-jia, FENG Wei, ZHENG Tong-yan   

  1. China Earthquake Networks Center, Beijing 100045, China
  • Received:2010-10-21 Revised:2011-01-10 Online:2011-04-30 Published:2021-09-09

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摘要： 破坏性地震发生后, 相关部门须启动适当的应急响应等级并按照应急预案开展救灾。 对响应等级的判断可视为对一个地震灾害事件严重程度分类判别的问题。 贝叶斯判别分析法是一种应用广泛的判别分析统计方法, 本文论述了贝叶斯判别分析法在判断地震应急响应等级中的应用; 通过对1949—2008年中国大陆成灾震例的整理分析, 以震级、 震区人口密度等地震有关信息为依据, 建立起地震应急响应等级的分类判别规则, 从而提供了一种简便、 快速的地震应急响应等级初判方法; 经检验该方法是有效的。

关键词: 地震应急响应等级, 震区人口密度, 贝叶斯判别分析法

Abstract: Once a devastating earthquake hits China continent, the relevant departments should start certain appropriate emergency response level to provide disaster relief according to the emergency plan. Judging a quake emergency response level is something equivalent to classifying the quake by the disaster scale that it caused. Bayesian classification analytical method is a common and widely used statistic method. This paper discusses the Bayesian classification analytical method applied to early judgment of earthquake emergency response level. Taking information about a quake (e.g. magnitude and population density of an area around the epicenter, etc.) as the parameters, classification rules for earthquake emergency response level are established through the analysis of the China continent earthquake samples that caused disasters in the year between 1949 and 2008. Consequently, a simple and quick early judgment method of earthquake emergency response level is derived. The method is effective by test.

Key words: Earthquake emergency response level, Bayesian classification analytical method, Magnitude, Population density of the area around the epicenter

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