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河北及邻区地震时空概率增益综合预测研究
齐玉妍1) 孙丽娜1) 邱玉荣2) 李姜1) 金学申1)
1)河北省地震局,石家庄市槐中路262 号050021; 2)陕西省地震局,西安710068
摘要:
结合地震空间分布非均匀性指标Kcv值预测方法和图像信息学算法对河北及邻区2013 ~ 2017 年ML≥5. 0 地震发生概率增益进行预测。根据河北及邻区40 多年的地震观测资料,对地震空间分布非均匀性指标Kcv值进行了空间扫描和震例统计,得到了此方法应用于河北地区的预测效能,并对河北及邻区2013 ~ 2017 年ML≥5. 0 地震发生概率增益进行了预测;对图像信息学算法在研究区进行了地震危险性概率预测的回溯性检验,得到了此方法应用于研究区的预测效能R 值及概率增益K 值,并进行了5 年尺度的地震危险性预测。在上述2 个单项预测方法的基础上,基于概率增益综合预测模型,得到了5 年尺度河北及邻区ML≥5. 0 地震发生概率增益的综合预测结果。
关键词:  Kcv值  概率增益  图像信息学  地震预测
DOI:
分类号:
基金项目:河北省地震科技星火计划重点课题“基于单项预测效能的综合概率增益预测模型研究———以华北地区为例”资助
The synthetical prediction research on earthquake spatial and temporal probability gain in Hebei Province and its adjacent areas
Qi Yuyan1) Sun Lina1) Qiu Yurong2) Li Jiang1) Jin Xueshen1)
1) Earthquake Administration of Hebei Province,Shijiazhuang 050021,China;2) Earthquake Administration of Shaanxi Province,Xi’an 710068,China
Abstract:
In this paper,the probability gain is synthesized by the forecasting method of heterogeneity parameter Kcv of spatial distribution of earthquake and Pattern Informatics algorithm, which provides a way of predicting the ML≥5. 0 earthquake probability gain from 2013 to 2017 in Hebei Province and its adjacent areas. According to earthquake observation data of more than 40 years in Hebei Province and its adjacent areas,the efficiency of earthquake prediction for the seismic spatial heterogeneity index method is researched by spatial scanning Kcv-value and earthquake cases statistics,and then the ML≥5. 0 earthquake probability gain forecasting from 2013 to 2017 in Hebei Province and its adjacent areas is provided. The retrospective test of Pattern Informatics algorithm for seismic hazard probability prediction in the study area is carried out,the prediction R-value and probability gain K value of the method is obtained,and the forward prediction for five years is given. Finally,synthetical prediction results of the ML≥5. 0 earthquake probability gain are obtained for the next 5 years in Hebei Province and its adjacent areas by the prediction of comprehensive probability gain of the above two single prediction methods.
Key words:  Kcv-value  Probability gain  Pattern informatics  Earthquake prediction