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自然灾害概率风险历史资料的有效性及其检验
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  • 英文篇名:Validity Analysis of Historical Data for Probabilistic Risk Analysis in Natural Disaster
  • 作者:郭君 ; 孔锋
  • 英文作者:GUO Jun;KONG Feng;School of Public Policy and Management,Tsinghua University;Center for Crisis Management Research,Tsinghua University;Center for Social Risk Assessment in China,Tsinghua University;
  • 关键词:自然灾害 ; 概率风险 ; 动态风险 ; 历史资料 ; 有效性 ; 变点检验
  • 英文关键词:natural disaster;;probabilistic risk;;dynamic risk;;historical data;;validity analysis;;abrupt change test
  • 中文刊名:ZHXU
  • 英文刊名:Journal of Catastrophology
  • 机构:清华大学公共管理学院;清华大学应急管理研究基地;清华大学中国社会风险评估研究中心;
  • 出版日期:2019-07-08
  • 出版单位:灾害学
  • 年:2019
  • 期:v.34;No.133
  • 基金:中国博士后科学基金资助项目(2018M631510;2019T120113);; 国家自然科学基金项目(41801064;71790611)
  • 语种:中文;
  • 页:ZHXU201903005
  • 页数:6
  • CN:03
  • ISSN:61-1097/P
  • 分类号:24-29
摘要
动态变化的自然-社会系统导致自然灾害风险处于动态变化中,久远的历史资料可能不是概率风险评估的有效样本,然而目前基于历史记录的概率风险评估尚未对使用的一段时间历史资料的有效性加以说明。鉴于此,通过指出自然灾害风险系统和历史记录统计口径具有动态变化性,揭示历史记录资料存在有效性问题,即一段时期的历史灾害记录序列可能存在变点,继而将变点检验方法引入自然灾害概率风险历史资料有效性检验。当前变点检验的方法众多,包括最小二乘法、广义似然比检验、贝叶斯方法、局部比较法、非参数方法等,针对具体的问题需选择合适的方法。研究指出的历史资料有效性问题,希望对后续历史资料选取的理念、选取后的风险评估理论和实践应用等方面提供参考意义,以期从数据使用层面提高灾害风险评估结果的可靠性。
        With the changes in the nature and the society,natural disaster risks will inevitably change. Some historical data at earlier period time would be invalid for probabilistic risk analysis. However,few studies have illustrated the selection of the historical data for probabilistic risk analysis in natural disaster nowaways. Therefore,this paper points out that historical data might be invalid due to the dynamics of natural disaster risk system and the change of statistical caliber for historical data. What's more,this paper trys to introduce abrupt change test methods into the validity analysis of historical data for probabilistic risk analysis in natural disaster. There are many kinds of abrupt change test methods and each method has its advantages and limitations. Proper method should be chosen for different change point problems in validity analysis of historical data. This study aims to improve the reliability of probabilistic risk analysis for natural disaster in data collection.
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