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Title:: Precursor Anomaly Identification Based on Earthquake Corresponding Probability Spectrum Analysis

作者:: 王海涛¹; 2; 王琼²; (1.中国地震局地震预测研究所兰州科技创新基地,兰州 730000; 2.新疆维吾尔自治区地震局,乌鲁木齐 830011)

Author(s):: WANG Hai-tao¹; 2; WANG Qiong²; (1.Lanzhou Base of Institute of Earthquake Science,CEA,Lanzhou 730000,China)(2.Earthquake Administration of Xinjiang Uygur Autonomous Region,Urumqi 830011,China)

Keywords:: earthquake corresponding probability spectrum; sliding mean probability; precursor anomaly; identification quantification

摘要:: 针对观测或分析资料曲线异常的定量化识别提取问题,研究提出了地震对应概率谱统计方法和累计滑动平均概率分析方法。通过地震对应谱分析可以得到不同值域数据异常信度属性。在不同考察时长的对应概率谱基础上,将原始数据时间序列转换成概率时间序列,并采用多点累计滑动平均方法得到滑动平均概率时间进程曲线,进而进行地震前兆异常的识别研究。以新疆北天山地区地震学参数η值时间进程序列为原始数据进行算例分析,结果显示,当考察时长为18个月时,利用滑动平均概率时间进程曲线可以较好地识别地震前兆异常,异常对应率为83%,有震报准率为86%,异常具有中期属性。分析认为,不同考察时长的地震对应概率谱和滑动平均概率序列,不仅可以用于单项资料的前兆异常识别研究,还可以为综合分析预报提供定量的单项因子数据。

Abstract:: With the aim to the quantification of anomaly identification and extraction for observed or analyzed records,we present earthquake corresponding probability spectrum statistical method and cumulative sliding mean probability analysis method.By earthquake probability spectrum analysis,we can obtain the abnormal confidence attribute of data in different value ranges.Based on the probability spectrum in different studied time-intervals,we convert the original data time sequence into probability time sequence,and can obtain the time curve for sliding mean probability by using multi-point cumulative sliding mean method,then identify seismic precursor anomaly.Taking the time sequence of η-value in the North Tianshan region as original data,we test the methods.The result shows that when the studied time-interval is 18 months,the precursor anomaly can be identified better from sliding mean probability time curve.The anomaly corresponding rate is 83 per cent,earthquake corresponding rate 86 per cent,and the anomaly is in middle term.The analysis indicates that the earthquake corresponding probability spectrum and sliding mean probability sequence in different time-intervals may not only be used to identify the precursor anomaly of single-item data,but also offer the data of quantitative single-item anomdy for comprehensive earthquake analysis and prediction.