Article
Version 2
Preserved in Portico This version is not peer-reviewed
Earthquake Footprints for Predicting Events
Version 1
: Received: 6 July 2023 / Approved: 7 July 2023 / Online: 10 July 2023 (10:13:40 CEST)
Version 2 : Received: 10 July 2023 / Approved: 11 July 2023 / Online: 11 July 2023 (13:13:11 CEST)
Version 3 : Received: 7 August 2023 / Approved: 8 August 2023 / Online: 8 August 2023 (12:02:08 CEST)
Version 2 : Received: 10 July 2023 / Approved: 11 July 2023 / Online: 11 July 2023 (13:13:11 CEST)
Version 3 : Received: 7 August 2023 / Approved: 8 August 2023 / Online: 8 August 2023 (12:02:08 CEST)
How to cite: Greer, K. Earthquake Footprints for Predicting Events. Preprints 2023, 2023070584. https://doi.org/10.20944/preprints202307.0584.v2 Greer, K. Earthquake Footprints for Predicting Events. Preprints 2023, 2023070584. https://doi.org/10.20944/preprints202307.0584.v2
Abstract
This paper considers the problem of predicting earthquakes. It uses a small amount of information to create a descriptive key that can be used as a footprint to describe an event. A frequency grid clusters events that occurred at the same time and then the algorithm measures the history of these events over preceding days, in particular the gaps when the events did not occur. The clusters with the time gaps can be used to create the footprint description and results suggest that seismic events can in fact be traced using this, and subsequently recognised again, if the same conditions occur. Greek and USA datasets have been looked at and the prediction accuracy can be 70% or better. The author therefore suggests that this is an interesting method that deserves attention.
Keywords
earthquake, footprint, predict events, cluster, frequency grid
Subject
Environmental and Earth Sciences, Geophysics and Geology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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