Abstract

The database obtained from the observations of the Italian Seismological Network over more than 15 yr was analyzed by a simple algorithm to determine the rate of occurrence of major events after the precursors called foreshocks: moderate earthquakes following a period of quiescence. The number of observed foreshocks depends, among other factors, on the spatial (R1) and temporal (T1) ranges of the quiescence used to define the foreshocks. These parameters can be optimized to get the highest value of the success rate of the precursor for a given data set. In our case, the optimization process led to a probability gain (G) higher than 100. In order to estimate the factors that influence the value of G, we tested our method on synthetic catalogs obtained from the real one by randomizing the origin times of the events, or the spatial coordinates, or both of them. The analysis showed that the apparently high value of the probability gain obtained optimizing the parameters. R1 and T1 is the result of (a) shortness of the catalog, (b) uneven spatial distribution of seismicity, and (c) real variation in time of the occurrence rate.

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