Machine‐Learning‐Based Analysis of the Guy‐Greenbrier, Arkansas Earthquakes: A Tale of Two Sequences-Reference-Cited by-同舟云学术

Machine‐Learning‐Based Analysis of the Guy‐Greenbrier, Arkansas Earthquakes: A Tale of Two Sequences

Published:2020-03-18 Issue:6 Volume:47 Page:
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophys. Res. Lett.

Author:

Park Yongsoo¹^ORCID,Mousavi S. Mostafa¹^ORCID,Zhu Weiqiang¹,Ellsworth William L.¹^ORCID,Beroza Gregory C.¹^ORCID

Affiliation:

1. Department of Geophysics Stanford University Stanford CA USA

Funder

U.S. Department of Energy

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020GL087032

Reference25 articles.

1. Maximum likelihood estimate of b in the formula logN=a−bM and its confidence limits;Aki K.;Bulletin of the Earthquake Research Institute, Tokyo University,1965

2. Machine learning for data-driven discovery in solid Earth geoscience

3. Temporal variation of seismicb-values beneath northeastern Japan island arc

4. Disposal of Hydrofracking Waste Fluid by Injection into Subsurface Aquifers Triggers Earthquake Swarm in Central Arkansas with Potential for Damaging Earthquake

5. Temporal variation in the magnitude‐frequency distribution during the Guy‐Greenbrier earthquake sequence

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