Kriging parameter optimisation: global versus local search strategies

C. R.A.F. Fonseca, J. F.C.L. Costa, R. Hundelshaussen, M. A.A. Bassani

Producción científica: Contribución a una revistaArtículo en revista científica indexadarevisión exhaustiva

1 Cita (Scopus)


Kriging methods require parameters to define search strategy (kriging neighbourhood). These parameters affect the precision and accuracy of its estimates. Frequently, the choice of these parameters is merely subjective. Some practitioners prioritise estimates that lead to models with a reduced smoothing effect or a regression slope as close as possible to one. However, it is prevalent to use the same kriging neighbourhood or search strategy for all blocks estimated within a stationary domain. This study presents a contribution that challenges this concept by using a block-by-block optimisation approach focused on the localised kriging parameter optimisation (LKPO) methodology. A comparative study is carried out, and some of the metrics analysed include the kriging efficiency and the slope of regression (typical in optimising methodologies in the mining industry). The results indicate that the LKPO methodology provides more accurate and precise estimates than those based on a global kriging neighbourhood.

Idioma originalInglés
Páginas (desde-hasta)185-196
Número de páginas12
PublicaciónApplied Earth Science: Transactions of the Institute of Mining and Metallurgy
EstadoPublicada - 2021
Publicado de forma externa

Nota bibliográfica

Publisher Copyright:
© 2021 Institute of Materials, Minerals and Mining and The AusIMM.


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