ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Pure and applied geophysics 145 (1995), S. 259-275 
    ISSN: 1420-9136
    Keywords: Seismicity ; earthquake prediction ; seismotectonic ; regionalization ; Italy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: 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.
    Type of Medium: Electronic Resource
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...