Titre :

Modeling spatial dynamics of the Fani Maoré marine volcano earthquake data

Auteur(s) :

Manou-Abi, Solym [Auteur correspondant]
Centre Universitaire de Formation et de Recherche de Mayotte (CUFR) [CUFR]
Institut Montpelliérain Alexander Grothendieck [IMAG]
Hachim, Said Said [Auteur]
Dabo-Niang, Sophie [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Nguala, Jean-Berky [Auteur]
Laboratoire d'Informatique et de Mathématiques [LIM]
Centre Universitaire de Formation et de Recherche de Mayotte (CUFR) [CUFR]

Mot(s)-clé(s) en anglais :

Classification Spatio-temporal model Time series Spatial point pattern analysis Earth Science Spatial density smoothing
Classification
Spatio-temporal model
Time series
Spatial point pattern analysis
Earth Science
Spatial density smoothing

Discipline(s) HAL :

Mathématiques [math]/Statistiques [math.ST]

Résumé en anglais : [en]

This paper provides the outcomes of a work consisting in modeling and learning some earthquakes data collected during the Mayotte seismovolcanic crisis of 2018-2021. We highlight the performance of some process data models ...
Lire la suite >This paper provides the outcomes of a work consisting in modeling and learning some earthquakes data collected during the Mayotte seismovolcanic crisis of 2018-2021. We highlight the performance of some process data models in order to illustrate the spatial and temporal dynamic. Unsupervised clustering method, spatial pattern analysis, spatial density estimation through spatial marked point process; time series and spatio-temporal models are efficient tools that we studied in this paper to look for the spatial and temporal variation of such spatial data mainly driven by the detected underwater volcano around Mayotte called Fani Maoré. The dynamic of the magnitude and depth Spatial dynamics of the Fani Maoré marine volcano events of the Fani Maoré with the use of the above mentionned models seems to perform the data. We present a discussion thoughout the presentation of the obtained results together with the limit of this study and some forthcoming projects and modeling developments.Lire moins >

Langue :

Anglais

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL