The Automatic Identification Technology about Abnormal Activity Based on Seismic Prediction Efficiency

In this paper, eight seismic activity parameters, which are independent of each other with clear physical meanings, are selected and the special-temporal scanning method is adopted so as to establish an autocratic identification model for abnormal seismicity on the purpose of prediction. On this basis, seismic data (M L ≥2.0) collected from 1987 to 2009 in North China (30°~44°N, 106°~126°E) is selected to test the model. The results show that abnormal seismicity identification method can lower the false alarm rate and improve the capability of identifying the abnormal seismicity.