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With the aim to the quantification of anomaly identification and extraction for observed or analyzed records, we present two statistical methods of earthquake corresponding relevancy spectrum(ECRS)and sliding mean relevancy (SMR).With ECRS method,we can obtain the abnormal confidence attribute of data in different value ranges.Based on the relevancy spectrum in different studied time-intervals,we convert the original time sequence into relevancy time sequence, and can obtain the SMR time series by using the multi-point cumulative sliding mean method.Then we can identify the seismic precursor anomaly.We test this method by taking the time sequence ofη-value in the northern Tianshan region as original data.The result shows that when the studied time-interval is 18 months,the precursor anomaly can be identified better from sliding mean relevancy.The anomaly corresponding rate is 83 percent,the earthquake corresponding rate is 86 percent,and the anomaly is characteristic of the middle term.To try the research on multi-parameter comprehensive application, we take the Kalpin tectonic block in Xinjiang as our studied region,and analyze the spatial and temporal abnormal characters of multi-parameter sliding extreme-value relevancy(MSER)before mid-strong earthquakes in the Kalpin block.The result indicates that ECRS and SMR sequence in different time-intervals can not only be used to identify the precursor anomaly of single-item data,but also offer the data of quantitative single-item anomaly for comprehensive earthquake analysis and prediction.
With the aim to the quantification of anomaly identification and extraction for observed or analyzed records, we present two statistical methods of earthquake corresponding relevancy spectrum (ECRS) and sliding mean relevancy (SMR) .With ECRS method, we can obtain the abnormal confidence attribute of data in different value ranges.Based on the relevancy spectrum in different studied time-intervals, we convert the original time sequence into relevancy time sequence, and can obtain the SMR time series by using the multi-point cumulative sliding mean method. identify the seismic precursor anomaly. We test this method by taking the time sequence of η-value in the northern Tianshan region as original data. The result shows that when the studied time-interval is 18 months, the precursor anomaly can be identified better from sliding mean relevancy.The anomaly corresponding rate is 83 percent, the earthquake corresponding rate is 86 percent, and the anomaly is characteristic of the middle ter m.To try the research on multi-parameter comprehensive application, we take the Kalpin tectonic block in Xinjiang as our studied region, and analyze the spatial and temporal abnormal characters of multi-parameter sliding extreme-value relevancy (MSER) before mid-strong earthquakes in the Kalpin block. The result indicates that ECRS and SMR sequences in different time-intervals can not only be used to identify the precursor anomaly of single-item data, but also offer the data of quantitative single-item anomaly for comprehensive earthquake analysis and prediction.