nach oben

Earth Science Informatics

Erschienen in:

09.10.2020 | Research Article

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

verfasst von: K. Florios, I. Contopoulos, G. Tatsis, V. Christofilakis, S. Chronopoulos, C. Repapis, Vasilis Tritakis

Erschienen in: Earth Science Informatics | Ausgabe 1/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

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.

Vorheriger Artikel GIS-based multi-criteria decision making and entropy approaches for groundwater potential zones delineation

Nächster Artikel A hybrid SVR-PSO model to predict concentration of sediment in typical and debris floods

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

Bobra MG, Couvidat S (2015) Solar flare prediction using SDO/HMI vector magnetic field data with a machine-learning algorithm. Astrophys J 798:135–145CrossRef

Breiman L (2001) Random forests. Mach Learn 45(1):5–32CrossRef

Christofilakis V, Tatsis G, Votis G, Contopoulos I, Repapis C, Tritakis V (2019) Significant ELF perturbations in the Schumann resonance band before and during a shallow mid-magnitude seismic activity in the Greek area (Kalpaki). J Atmos Sol Terr Phys 182:138–146CrossRef

Filizzola C et al (2004) Robust satellite techniques for seismically active areas monitoring: a sensitivity analysis on September 7, 1999 Athens's earthquake. Phys Chem Earth,PA/B/C 29(4–9):517–527CrossRef

Galar M, Fernández A, Barrenechea E, Bustince H, Herrera F (2012) “Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches”. https://doi.org/10.1109/TSMCC.2011.2161285

Greene WH (2002) Econometric analysis, 5th edn. Prentice Hall, Upper Saddle River

Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: data mining, inference and prediction (2nd edn)

Hayakawa M, Molchanov OA (2007) Seismo-electromagnetics as a new field of Radiophysics: electromagnetic phenomena associated with earthquakes. U.R.S.I. Radio Sci Bull No. 320, p. 8–17

Hayakawa M, Ohta K, Nickolaenko AP, Ando Y (2005) Anomalous effect in Schumann resonance phenomena observed in Japan, possibly associated with the chi-chi earthquake in Taiwan. Ann Geophys 23:1335–1346CrossRef

Hayakawa M, Nickolaenko AP, Sekiguchi M, Yamashita K, Ida Y, Yano M (2008) Anomalous ELF phenomena in the Schumann resonance band as observed at Moshiri (Japan) in possible association with an earthquake in Taiwan. Nat Hazards Earth Syst Sci 8:1309–1316CrossRef

Kapiris P et al (2005) Distinguished seismological and electromagnetic features of the impending global failure: Did the 7/9/1999 M5.9 Athens earthquake come with a warning? Earth Planets Space 57:215–230CrossRef

Karamanos K, Perantzakis A, Kapiris P, Nikolopoulos S, Kopanas J, Eftaxias K (2005) Extracting pre-seismic electromagnetic signatures in terms of symbolic dynamics. Nonlinear Process Geophys 12:835–848CrossRef

Karamanos K, Dakopoulos D, Aloupis K, Peratzakis A, Athanasopoulou L, Nikolopoulos S, Kapiris P, Eftaxias K (2006) Pre-seismic electromagnetic signals in terms of complexity. Phys Rev E 74:016104CrossRef

Liaw A, Wiener M (2002) Classification and regression by randomforest. R News 2(3):18–22

Mason JP, Hoeksema JT (2010) Testing automated solar flare forecasting with 13 years of Michelson Doppler imager Magnetograms. Astrophys J 723:634–640CrossRef

Pulinets S, Ouzounov D (2016) Earthquake precursors in atmosphere and ionosphere. A review and future prospects. EGU general assembly 2016, Vienna Austria, id. EPSC2016-3466

R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

Schumann WO (1952) On the free oscillations of a conducting sphere which is surrounded by an air layer and an ionosphere shell. Z Naturforschaftung 7a:149–154 (in German)CrossRef

Tatsis G, Votis G, Christofilakis V, Kostarakis P, Tritakis V, Repapis C (2015) A prototype data acquisition and processing system for Schumann resonance measurements. J Atmos Sol Terr Phys 135:152–160CrossRef

Tatsis G, Votis C, Christofilakis V, Kostarakis P, Tritakis V, Repapis C, Kalavrezos P (2016) Preliminary measurements of Schumann’s resonances (SR) in the Greek area. J Eng Sci Technol Rev 9(4):61–64CrossRef

Torgo L (2010) Data mining with R, learning with case studies chapman and hall/CRC. URL: http://www.dcc.fc.up.pt/~ltorgo/DataMiningWithR

Votis C, Tatsis G, Christofilakis V, Chronopoulos S, Kostarakis P, Tritakis V, Repapis C (2018) A new portable ELF Schumann resonance receiver: design and detailed analysis of the antenna and the analog front-end. EURASIP J Wirel Commun Netw, Open Access https://doi.org/10.1186/s13638-018-1157-7

Xinyang O, Xuemin Z, Nickolaenko AP, Hayakawa M, Xuhui S, Yuanqin M (2013) Schumann resonance observation in China and anomalous disturbance possibly associated with Tohoku M9.0 earthquake. Earth Sci 26(2):137–145CrossRef

Zhang H, Zimmerman J, Nettleton D, Nordman DJ (2019) Random Forest prediction intervals. Am Stat:1–15. https://doi.org/10.1080/00031305.2019.1585288

Titel: Possible earthquake forecasting in a narrow space-time-magnitude window
verfasst von: K. Florios
I. Contopoulos
G. Tatsis
V. Christofilakis
S. Chronopoulos
C. Repapis
Vasilis Tritakis
Publikationsdatum: 09.10.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Earth Science Informatics / Ausgabe 1/2021
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-020-00535-9

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2021

Energy efficiency maximization algorithm for underwater Mobile sensor networks

Investigating the historical development of accuracy and precision of Galileo by means of relative GNSS analysis technique

Analytical modeling of effect of volume of shale different calculation methods on reservoir petrophysical parameters

Neural network boosted with differential evolution for lithology identification based on well logs information

Analyzing surface air temperature and rainfall in univariate framework, quantifying uncertainty through Shannon entropy and prediction through artificial neural network

Street-block collapsed buildings assessment: A case study of Banqiao District, New Taipei City