Foreshock Detection Algorithms

Foreshock Detection Algorithms is a class of computational methodologies within seismological signal processing that are specifically designed to identify precursory seismic events preceding major earthquakes by distinguishing statistically anomalous patterns in foreshock sequences from background seismicity.

28

Publications

1.7K

Citations

77

Authors

45

Institutions

Publications per year

2017–2026

16

Authors

77

  1. TL
    Thorne Lay

    University of California, Santa Cruz, United States

    4 publications · 89 citations

    4

    h-index

  2. EE
    E. E. Brodsky

    University of California, Santa Cruz, United States

    4 publications · 89 citations

    4

    h-index

  3. AJ
    A. J. Meltzner

    Nanyang Technological University, Singapore

    2 publications · 47 citations

    2

    h-index

  4. SW
    Stefan Wiemer

    ETH Zurich, Switzerland

    2 publications · 402 citations

    2

    h-index

  5. ZP
    Zhigang Peng

    Georgia Institute of Technology, United States

    2 publications · 22 citations

    2

    h-index

1–5 of 77

Venues

  1. Seismological Research Letters

    SRL · 6 publications · 115 citations

    6

    h-index

  2. Bulletin of the Seismological Society of America

    BSSA · 5 publications · 138 citations

    5

    h-index

  3. Geophysical Research Letters

    3 publications · 227 citations

    3

    h-index

  4. Journal of Geophysical Research Solid Earth

    3 publications · 487 citations

    3

    h-index

  5. 1

    h-index

1–5