Springer Online Journal Archives 1860-2000
Abstract The algorithm CN makes use of normalized functions. Therefore the original algorithm, developed for the California-Nevada region, can be directly applied, without adjustment of the parameters, to the determination of the Time of Increased Probability (TIP) of strong earthquakes for Central Italy. The prediction is applied to the events with magnitudeM≥M 0=5.6, which in Central Italy have a return period of about six years. The routinely available digital earthquake bulletins of the Istituto Nazionale di Geofisica (ING), Rome, permits continuous monitoring. Here we extend to November 1994 the first study made by Keilis-Boroket al. (1990b). On the basis of the combined analysis of seismicity and seismotectonic, we formulate a new regionalization, which reduces the total alarm time and the failures to predict, and narrows the spatial uncertainty of the prediction with respect to the results ofKeilis-Borok et al. (1990b). The premonitory pattern is stable when the key parameters of the CN algorithm and the duration of the learning period are changed, and when different earthquake catalogues are used. The anlysis of the period 1904–1940, for whichM 0=6, allows us to identify self-similar properties between the two periods, in spite of the considerably higher seismicity level of the earlier time interval compared with the recent one.
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