Accéder directement au contenu Accéder directement à la navigation
Communication dans un congrès

Domaining by clustering multivariate geostatistical data

Abstract : Domaining is very often a complex and time-consuming process in mining assessment. Apart from the further delineation of envelopes, a significant number of parameters (lithology, alteration, grades?) are to be combined in order to characterize domains or sub domains. This rapidly leads to a huge combinatory. Hopefully the number of domains should be limited, while ensuring their connectivity as well as the stationarity of the variables within each domain. In order to achieve this goal, different methods for the spatial clustering of multivariate data are explored and compared. A particular emphasis is placed on the ways to modify existing procedures of clustering in non spatial settings to enforce the spatial connectivity of the resulting clusters. K-means, spectral methods and EM-based algorithms are reviewed. The methods are illustrated on mining data.
Type de document :
Communication dans un congrès
Liste complète des métadonnées

Littérature citée [9 références]  Voir  Masquer  Télécharger

https://hal-mines-paristech.archives-ouvertes.fr/hal-00776725
Contributeur : Thomas Romary <>
Soumis le : mercredi 16 janvier 2013 - 19:14:40
Dernière modification le : jeudi 24 septembre 2020 - 16:34:09
Archivage à long terme le : : mercredi 17 avril 2013 - 03:52:15

Fichier

paper_oslo.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00776725, version 1

Citation

Thomas Romary, Jacques Rivoirard, Jacques Deraisme, Cristian Quinones, Xavier Freulon. Domaining by clustering multivariate geostatistical data. Ninth International Geostatistics Congress,, 2012, Norway, France. pp.455-466. ⟨hal-00776725⟩

Partager

Métriques

Consultations de la notice

344

Téléchargements de fichiers

1407