Highlights In Chile a powerful earthquake of Mw =8.8 took place on February 27, 2010. This paper presents an application of ensemble methods to detect the TEC anomalies. Decision Tree, Bagging and Random Forest are proposed in the field of precursors. The proposed methods deserve serious attention as new predictor tools.

    Abstract In this paper for the first time ensemble methods including Decision Tree, Bagging and Random Forest have been proposed in the field of earthquake precursors to detect GPS-TEC (Total Electron Content) seismo-ionospheric anomalies around the time and location of Chile earthquake of 27 February 2010. All of the implemented ensemble methods detected a striking anomaly in time series of TEC data, 1day after the earthquake at 14:00UTC. The results indicate that the proposed methods due to their performance, speed and simplicity are quite promising and deserve serious attention as a new predictor tools for seismo-ionospheric anomalies detection.


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    Titel :

    Decision Tree, Bagging and Random Forest methods detect TEC seismo-ionospheric anomalies around the time of the Chile, (Mw =8.8) earthquake of 27 February 2010


    Beteiligte:

    Erschienen in:

    Advances in Space Research ; 57 , 12 ; 2464-2469


    Erscheinungsdatum :

    2016-03-24


    Format / Umfang :

    6 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch