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Possibility of short-term probabilistic forecasts for large earthquakes making good use of the limitations of existing catalogs
Author(s) -
Yoshito Hirata,
Koji Iwayama,
Kazuyuki Aihara
Publication year - 2016
Publication title -
physical review. e
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.896
H-Index - 304
eISSN - 2470-0053
pISSN - 2470-0045
DOI - 10.1103/physreve.94.042217
Subject(s) - term (time) , probabilistic logic , computer science , statistical physics , seismology , physics , geology , artificial intelligence , quantum mechanics
Earthquakes are quite hard to predict. One of the possible reasons can be the fact that the existing catalogs of past earthquakes are limited at most to the order of 100 years, while their characteristic time scale is sometimes greater than that time span. Here we rather use these limitations positively and characterize some large earthquake events as abnormal events that are not included there. When we constructed probabilistic forecasts for large earthquakes in Japan based on similarity and difference to their past patterns-which we call known and unknown abnormalities, respectively-our forecast achieved probabilistic gains of 5.7 and 2.4 against a time-independent model for main shocks with the magnitudes of 7 or above. Moreover, the two abnormal conditions covered 70% of days whose maximum magnitude was 7 or above.

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