Possible earthquake forecasting in a narrow space-time-magnitude window

We analyzed an extended time series of Schumann Resonance recordings with two multi-parametric statistical methods, the generalized linear Logistic Regression—LogReg and the non-linear Random Forest—RF, in order to test their potential for earthquake prediction within a narrow time-space-magnitude w...

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Bibliographic Details
Published in:Earth science informatics 2021-03, Vol.14 (1), p.349-364
Main Authors: Florios, K., Contopoulos, I., Tatsis, G., Christofilakis, V., Chronopoulos, S., Repapis, C., Tritakis, Vasilis
Format: Article
Language:English
Subjects:
Earth and Environmental Science
Earth Sciences
Earth System Sciences
Earthquake forecasting
Earthquake magnitude scale
Earthquake prediction
Earthquakes
Information Systems Applications (incl.Internet)
Ontology
Regression analysis
Research Article
Resonance
Schumann resonances
Seismic activity
Simulation and Modeling
Space Exploration and Astronautics
Space Sciences (including Extraterrestrial Physics
Statistical analysis
Statistical methods
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Summary:We analyzed an extended time series of Schumann Resonance recordings with two multi-parametric statistical methods, the generalized linear Logistic Regression—LogReg and the non-linear Random Forest—RF, in order to test their potential for earthquake prediction within a narrow time-space-magnitude window of 48 h, 250 km from our observing site, and events higher than magnitude 4 of the Richter scale. The LogReg method identified the power of the signal within our 10-min recording intervals as the main seismic precursor parameter. The RF method obtained promising results that will improve with continuous enrichment of the running data sample with new data. We conclude that a systematic analysis of Schumann Resonance recordings may lead to satisfactory levels of seismic prediction.
ISSN:1865-0473
1865-0481
DOI:10.1007/s12145-020-00535-9