 |
 |
Conference papers
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.
Cited literature [9 references]
https://hal-mines-paristech.archives-ouvertes.fr/hal-00776725
Contributor : Thomas Romary Connect in order to contact the contributor
Submitted on : Wednesday, January 16, 2013 - 7:14:40 PM
Last modification on : Wednesday, November 17, 2021 - 12:31:18 PM
Long-term archiving on: : Wednesday, April 17, 2013 - 3:52:15 AM
Contributor : Thomas Romary Connect in order to contact the contributor
Submitted on : Wednesday, January 16, 2013 - 7:14:40 PM
Last modification on : Wednesday, November 17, 2021 - 12:31:18 PM
Long-term archiving on: : Wednesday, April 17, 2013 - 3:52:15 AM
File
paper_oslo.pdf
Files produced by the author(s)