基于概率密度分布的地电场地震前兆异常提取方法

Abstract

Abstract: With improvement of geoelectrical field observation technology, there is a great deal of tectonic information in high-frequency sampling observational data. How to extract useful earthquake precursor from these data is a key problem. We introduced the PDF(probability density function)method, analyzed the observational data of 9 geoelectrical stations near the epicenter of the Lushan M_S7.0 earthquake and Minxian and Zhangxian M_S6.6 earthquake. The results show that three geoelectrical data had high-frequency anomalies before the two earthquakes. On the basis of these results, we considered that PDF method has certain reliability and applicability to extract the high-frequency anomaly information from geoelectrical observational data.

Key words: Geoelectrical field, Earthquke Prediction, Probability density distribution, High-frequency abnormal information

CLC Number:

P315.7

YU Chen,LU Jun,XIE Tao,YUE Chong,WANG Shu-yan. Extracting Earthquake Precursors from Geoelectrical Data based on Probability Density Distribution[J]. EARTHQUAKE, 2017, 37(4): 22-36.

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Extracting Earthquake Precursors from Geoelectrical Data based on Probability Density Distribution

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