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  Improved earthquake aftershocks forecasting model based on long-term memory

Zhang, Y., Zhou, D., Fan, J., Marzocchi, W., Ashkenazy, Y., Havlin, S. (2021): Improved earthquake aftershocks forecasting model based on long-term memory. - New Journal of Physics, 23, 042001.
https://doi.org/10.1088/1367-2630/abeb46

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 Creators:
Zhang, Yongwen1, Author
Zhou, Dong1, Author
Fan, Jingfang2, Author              
Marzocchi, Warner1, Author
Ashkenazy, Yosef1, Author
Havlin, Shlomo1, Author
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: A prominent feature of earthquakes is their empirical laws, including memory (clustering) in time and space. Several earthquake forecasting models, such as the epidemic-type aftershock sequence (ETAS) model, were developed based on these empirical laws. Yet, a recent study [1] showed that the ETAS model fails to reproduce the significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) discovered in the data. Our generalized ETAS model accurately reproduces the short- and long-term/distance memory observed in the Italian and Southern Californian earthquake catalogs. The revised ETAS model is also found to improve earthquake forecasting after large shocks.

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 Dates: 2021-04-082021-04
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1367-2630/abeb46
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
MDB-ID: Entry suspended
OATYPE: Gold Open Access
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Title: New Journal of Physics
Source Genre: Journal, SCI, Scopus, p3, oa
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Pages: - Volume / Issue: 23 Sequence Number: 042001 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1911272