Biblioteca - Ingemmet Search for 'an,phr: 16931'

Determination of variables in the prediction of strontium distribution coefficients for selected sediments

By Pace, Mary N.. Berlin Springer-Verlag 2001 . pp. 993-1002

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El rol del factor análisis y de regresión en la intepretación de datos en un reconocimiento geoquímico

By Closs, L. Graham. Lima INGEOMIN 1978 . 18 p. , Traducido del curso Geochemical Prospecting, in Adelaide-Australia, 1974

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Inferring injection returns from chloride monitoring data

By Sullera, Ma. Michelle. Oxford Elsevier Science 2001 . pp. 591-616

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Logistic regression for geologically constrained mapping of gold potential, Baguio district, Philippines

By Carranza, Emmanuel John M.. Ottawa, Ontario Canadian Institute of Mining, Metallurgy and Petroleum 2001 . pp. 165-175

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Correlación entre elementos químicos paso previo a la microscopía

By Manzaneda Cabala, José. Lima Sociedad Geológica del Perú 2008 . 6 p.

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Dependence of joint spacing on rock properties in carbonate strata

By Lézin, Carine. Tulsa, OK American Association of Petroleum Geologists 2009 . pp. 271-290

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Backward elimination procedure for a predictive model of gold concentration

By Samal, Abani R.. Amsterdam Elsevier Science 2008 . pp. 69-82

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Environmental factors controlling spatial variation in sediment yield in a central Andean mountain area

By Molina, Armando. Amsterdam Elsevier 2008 . pp. 176-186

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Downscaling MODIS-derived maps using GIS and boosted regression trees: The case of frost occurrence over the arid Andean highlands of Bolivia

By Pouteau, Robin. Amsterdam Elsevier 2011 . pp. 117-129

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Application of GIS and remote sensing techniques in generation of land use scenarios for hydrological modeling

By Onate Valdivieso, F.. Amsterdam Elsevier 2010 . pp. 256-263

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Automatic estimation of optimal autoregressive filters for the analysis of volcanic seismic activity

By Lesage, Philippe. Munich European Geosciences Union 2008 . pp. 369-376

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Hydrothermal alteration mapping through multivariate logistic regression analysis of lithogeochemical data

By Mokhtari, Ahmad Reza. Amsterdam Elsevier Science 2014 . pp. 207-212

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Monitoring selective logging in western Amazonia with repeat lidar flights

By Andersen, Hans-Erik. Amsterdam Elsevier 2014 . pp. 157-165

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The single component geochemical map: Fact or fiction?

By McKinley, Jennifer M.. Amsterdam Elsevier Science 2016 . pp. 16-28

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A machine learning approach to geochemical mapping

By Kirkwood, Charlie. Amsterdam Elsevier Science 2016 . pp. 49-61

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Mapping mineral prospectivity using an extreme learning machine regression

By Chen, Yongliang. Amsterdam Elsevier Science 2017 . pp. 200-213

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Mineral potential mapping using a conjugate gradient logistic regression model

By Lin, Nan. Berlin Springer 2020 . pp. 173-188

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Mapping mineral prospectivity via semi-supervised Random Forest

By Wang, Jian. Berlin Springer 2020 . pp. 189-202

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El rol del factor análisis y de regresión en la interpretación de datos en un reconocimiento geoquímico (traducción al español de Nestor Chacón Abad)

By Closs, L. Graham. Ottawa, Ontario National Research Council of Canada 1975 . pp. 1316-1330

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Time-series study of associations between rates of people affected by disasters and the El Niño Southern Oscillation (ENSO) cycle

By Lam, Holly Ching Yu. Basel MDPI 2019 . 16 p.

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Field data reveal that the transport probability of clasts in Peruvian and Swiss streams mainly depends on the sorting of the grains

By Schlunegger, Fritz. Gottingen Copernicus | European Geosciences Union 2020 . pp. 717-728

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