期刊文献+

地震分布非均匀性指标K_(cv)值及其在亚洲大地震预测中的应用研究 被引量:2

Heterogeneity Parameter Kcv of Earthquake Spatial Distribution and its Preliminary Application in Forecasting Great Earthquakes in Asia
下载PDF
导出
摘要 理论研究和实际预测表明地震空间分布非均匀性指标Cv值是一种有效的预测指标。但目前使用的Cv值在同一信度水平下,其置信区间大小与空间分布的事件样本数大小有关,不便于结果的分析比较。本文在Cv值基础上定义了一个新的预测指标Kcv,并基于强震时空概率增益预测模型及其单项预测方法预测效能检验的方法,依据亚洲地震重点研究区近20年来的地震活动空间分布非均匀性的研究与震例统计,建立了该方法预测大地震的经验概率增益谱与预测效能谱。在建立Kcv值预测地震的方法基础上,通过对2000—2009年研究区MW6.9以上地震发生概率和概率增益值预测并与实际地震发生情况的回溯性检验,探讨了本方法预测大地震的实际效果,在此基础上预测了2010—2019年亚洲重点研究区MW6.9以上地震发生的概率和概率增益。 The heterogeneity parameter Cv of spatial distribution of earthquake is an effective predictor of earthquakes.However,comparative analysis of their results is not very easy due to the uncertain relationship between the size of confidence interval and the size of the sample events of spatial distribution of Cv-value during the same level of reliability,which can impair its utility.In the present study,we defined a new parameter Kcv based on the parameter Cv.Further,according to the spatial-temporal probability gain model and the assessment method of efficiency of earthquake prediction methods,the empirical earthquake probability gain spectrum and efficiency spectrum of this novel method were calculated using the heterogeneity research and earthquake case statistics over the past 20 years.The robustness and effectiveness of Kcv-value method were further evaluated by analyzing its probability gain values,the probability of ≥MW6.9 earthquake occurrences from 2000 to 2009 and their actual test of retrospective predictions.Our approach provides a way of predicting the ≥MW6.9 earthquake probability and probability gain from 2010 to 2019,and providing a reference to determine Asian earthquake risk zones in the next decade.
出处 《地震》 CSCD 北大核心 2011年第3期27-36,共10页 Earthquake
基金 国家科技支撑计划重点课题(2008BAC44B02)资助
关键词 Kcv值 MONTE Carlo法 预测效能 概率增益 亚洲地区 Kcv-Value Monte Carlo Prediction performance Probability gain Asia
  • 相关文献

参考文献10

二级参考文献46

共引文献53

同被引文献24

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部