Comparison of kriging and neural networks with application to the exploitation of a slate mine
From MaRDI portal
Publication:702522
DOI10.1023/B:MATG.0000029300.66381.ddzbMath1098.86001OpenAlexW1980066536MaRDI QIDQ702522
J. Taboada, J. M. Matías, A. Vaamonde, Wenceslao González Manteiga
Publication date: 17 January 2005
Published in: Mathematical Geology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1023/b:matg.0000029300.66381.dd
Related Items (7)
Creating a quality map of a slate deposit using support vector machines ⋮ Comparison of machine learning methods for copper ore grade estimation ⋮ Ore grade prediction using a genetic algorithm and clustering based ensemble neural network model ⋮ Shape functional optimization with restrictions boosted with machine learning techniques ⋮ Partially linear support vector machines applied to the prediction of mine slope movements ⋮ Comparison of Kriging and artificial neural network models for the prediction of spatial data ⋮ Variography for model selection in local polynomial regression with spatial data
This page was built for publication: Comparison of kriging and neural networks with application to the exploitation of a slate mine
