An Adaptable Random Forest Model for the Declustering of Earthquake Catalogs-Reference-Cited by-同舟云学术

An Adaptable Random Forest Model for the Declustering of Earthquake Catalogs

Published:2022-02 Issue:2 Volume:127 Page:
ISSN:2169-9313
Container-title:Journal of Geophysical Research: Solid Earth
language:en
Short-container-title:JGR Solid Earth

Author:

Aden‐Antoniów F.¹²^ORCID,Frank W. B.¹^ORCID,Seydoux L.³⁴^ORCID

Affiliation:

1. Department of Earth, Atmospheric and Planetary Sciences Massachusetts Institute of Technology Cambridge MA USA

2. Now at GNS Science Lower Hutt New Zealand

3. Équipe Ondes et Structures ISTerre Université Grenoble‐Alpes Gières France

4. Now at Massachusetts Institute of Technology Cambridge MA USA

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Geochemistry and Petrology,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021JB023254

Reference89 articles.

1. An Adaptable Random Forest Model for the Declustering of Earthquake Catalogs

2. Statistical Analysis of the Preparatory Phase of the M w 8.1 Iquique Earthquake, Chile

3. Maximum likelihood estimate of b in the formula log n= a‐bm and its confidence limits;Aki K.;Bulletin of the Earthquake Research Institute, Tokyo University,1965

4. Earthquake magnitude prediction in Hindukush region using machine learning techniques

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