Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1160242
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dc.contributor.authorRODRIGUES, N. B.
dc.contributor.authorSILVA, J. C. L. daeng
dc.contributor.authorPINHEIRO, H. S. K.eng
dc.contributor.authorCARVALHO JUNIOR, W. deeng
dc.date.accessioned2023-12-27T13:32:31Z-
dc.date.available2023-12-27T13:32:31Z-
dc.date.created2023-12-27
dc.date.issued2023
dc.identifier.citationIn: CONGRESSO LATINO-AMERICANO DE CIÊNCIA DO SOLO, 23.; CONGRESSO BRASILEIRO DE CIÊNCIA DO SOLO, 38., 2023, Florianópolis. Anais [...]. Florianópolis: Epagri, 2023. p. 104. Ref. ID 1073.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1160242-
dc.descriptionThe study aimed to evaluate the performance of Multivariate Adaptive Regression Spline (MARS), Radial Support Vector Machine (svmRadial) and Random Forest (RF) models to predict the spatial distribution of Fe2O3, Nb and TiO2 contents in Morro dos Seis Lagos-AM, Brazil.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectPedometrics
dc.subjectMachine-learning
dc.subjectPoorly-accessible areas
dc.titleDigital mapping of Fe2O3, Nb and TiO2 contents in Morro dos Seis Lagos (AM).
dc.typeResumo em anais e proceedings
riaa.ainfo.id1160242
riaa.ainfo.lastupdate2023-12-27
dc.contributor.institutionNIRIELE BRUNO RODRIGUES, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO
dc.contributor.institutionJÚLIO CESAR LOPES DA SILVA, UNIVERSIDADE FEDERAL DO RIO DE JANEIROeng
dc.contributor.institutionHELENA SARAIVA KOENOW PINHEIRO, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIROeng
dc.contributor.institutionWALDIR DE CARVALHO JUNIOR, CNPS.eng
Appears in Collections:Resumo em anais de congresso (CNPS)

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