|本期目录/Table of Contents|

[1]袁伏全,孙世瑞,王小玲.PI算法用于青海地区中强震危险性预测的回溯性检验研究*[J].地震研究,2016,39(增刊):76-82.
 YUAN Fuquan,SUN Shirui,WANG Xiaoling.Retrospective Forecast Test Study on Seismic Risk Prediction of Medium-strong Earthquakes in Qinghai Region by PI Algorithm[J].Journal of Seismological Research,2016,39(增刊):76-82.
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PI算法用于青海地区中强震危险性预测的回溯性检验研究*(PDF/HTML)

《地震研究》[ISSN:1000-0666/CN:53-1062/P]

卷:
39
期数:
2016年增刊
页码:
76-82
栏目:
出版日期:
2016-11-20

文章信息/Info

Title:
Retrospective Forecast Test Study on Seismic Risk Prediction of Medium-strong Earthquakes in Qinghai Region by PI Algorithm
作者:
袁伏全孙世瑞王小玲
青海省地震局,青海 西宁 810001
Author(s):
YUAN FuquanSUN ShiruiWANG Xiaoling
Earthquake Administration of Qinghai Province,Xining 810001,Qinghai,China
关键词:
门源6.4级地震 PI算法 地震预测
Keywords:
Menyuan MS6.4 earthquake in 2016 PI algorithm earthquake forecast
分类号:
P315.75
DOI:
-
摘要:
利用PI算法对青海地区M≥5.0“目标震级”的地震进行显著危险区分析。采用10年尺度的地震“变化学习”时间段和3年尺度“预测”时间段分别统计1970~2015年中国地震台网中心和青海省地震台网目录,计算显著地震事件的发生概率,检测高概率发震区域(地震热点)。回溯性检验结果表明,2016年门源MS6.4地震震中附近存在PI图像“热点”; 未来3年(2016~2018年),门源—祁连、德令哈、兴海、玉树和唐古拉地区的热点值lg(△P/△Pmax)偏高; PI算法适用于青海地区中强地震的中长期预测。
Abstract:
The Pattern Informatics(PI)algorithm was applied to analyze M≥5.0 earthquakes in the Qinghai region. Using the catalogues of M≥5.0 earthquakes in Qinghai region provided by NEIC and Qinghai seismic network from 1970 to 2015,we made statistic by using “variation leaning” period in 10 years scale and the “prediction” period in 3 years scale respectively. The retrospective forecast test results show that there exit the “hotspot” around the epicenter of Menyuan MS6.4 earthquake in 2016 in PI diagram. In the next three years(2016~2018),the “hot spot” values lg(△P/△Pmax)are higher in the Menyuan-Qilian,Delingha,Xinghai,Yushu and Tanggula areas. It is shown that the PI method could be applied in the middle and long term prediction of the moderately strong earthquake in Qinghai area.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-08-23
基金项目:地震科技星火计划——利用显著强震研究巴颜喀拉地块边界的孕震机理(XH16039)和青海省地震科学基金——PI算法用于青海地区中强地震回潮性检验和危险性预测(2017A)联合资助.

更新日期/Last Update: 2016-10-20