Abstract:
Analysis and forecast of aftershocks of large earthquakes in the world practice is currently based exclusively
on stochastic models of aftershock process. This makes it possible to use statistical methods of analysis,
and also to apply the "scenario" approach in forecasts by repeatedly generating random sequences
of aftershocks and counting the frequency of repetition of the events of interest. Studies
on the Russian Science Foundation project "Development of information system for automatic seismic
hazard assessment after large earthquakes based on geophysical monitoring" in 2016-2018 showed
however that the effectiveness of such approaches has significant limitations. In this paper
I give a critical review of statistical methods for the analysis and forecast of aftershocks,
an interpretation of the effectiveness limits of forecasts using standard approaches, provide the
rationale for the need to change the paradigm. As one of the search directions, the application of
Discrete Mathematical Analysis (DMA) methods developed by Academician A.D. Gvishiani and his scientific school.
An obvious advantage of this approach is demonstrated by the example of a simple algorithm for identification
of aftershocks using fuzzy comparisons.
Keywords:aftershocks of earthquakes, Omori law, Gutenberg–Richter law, law of repeatability of the number of aftershocks, cluster, Discrete Mathematical Analysis, fuzzy sets, fuzzy comparisons.
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