SciELO - Scientific Electronic Library Online

 
vol.38 issue2An experimental study of surface roughness in electrical discharge machining of AISI 304 stainless steel author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Ingeniería e Investigación

Print version ISSN 0120-5609

Abstract

OCHOA, Luis H.; NINO, Luis F.  and  VARGAS, Carlos A.. Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques. Ing. Investig. [online]. 2018, vol.38, n.2, pp.97-103. ISSN 0120-5609.  https://doi.org/10.15446/ing.investig.v38n2.68407.

The purpose of this research is to apply methods of support vector machines (SVMs) for fast determination of earthquake depths using seismic records of the "El Rosal" station, near to the city of Bogotá - Colombia. The algorithm was trained with time signal descriptors of 863 seismic events acquired between January 1998 and October 2008. Only earthquakes with magnitude > 2 M_L were contemplated, filtering its signals to remove diverse kind of noises not related to earth tremors. During training stages of SVM several combinations of kernel function exponent and complexity factor were considered for time signals of 5, 10 and 15 seconds along with earthquake magnitudes of 2.0, 2.5, 3.0 and 3.5 M_L. The best classification of SVM was obtained using time signals of 15 seconds and earthquake magnitudes of 3.5 M_L with kernel exponent of 10 and complexity factor of 2, showing accuracy of 0,6 ± 16,5 kilometers, which is good enough to be used in an early warning system for the city of Bogotá. It is recommended to provide this model with more recent seismic events in order to improve its accuracy.

Keywords : Earthquake early warning; rapid response; earthquake depth; seismic event; Bogotá - Colombia; support vector machine regression (SVMR); seismology; earthquakes.

        · abstract in Spanish     · text in English     · English ( pdf )