Matches in SemOpenAlex for { <https://semopenalex.org/work/W3203634143> ?p ?o ?g. }
Showing items 1 to 44 of
44
with 100 items per page.
- W3203634143 endingPage "715" @default.
- W3203634143 startingPage "715" @default.
- W3203634143 abstract "The objective of this study was to estimate the volume of Eucalyptus spp clones (genus of rapid growth) in the Araripe Gypsum Pole, responsible for 97% of the national production of gypsum, employing the methodology of Artificial Neural Networks (ANNs) and comparing it with the volumetric models of schumacher and Hall and Spurr and also verify the efficiency of the estimation using different sample sizes and evaluate the contribution of a categorical variable in the estimation. Data came from an experiment implanted in the Experimental Station of the Agronomic Institute of Pernambuco, where was tested 15 clones of Eucalyptus spp planted in 2002, with final cut in 2009. It was also valued the adjustment of the best models for sample size. The goodness of fit of the models was evaluated based on: the adjusted coefficient of determination (R2aj), square root of the percent mean error (RMSE%), standard error estimate (Syx%) and an analysis graphic of the residues. The results obtained in the study showed that all modeling was adequate and it was observed that the efficiency of the adjustments depends not only on the sample size, but also on the variance, and that the addition of a categorical variable in the ANNs does not show any perceptible differences, necessary for volume estimation.e sample size." @default.
- W3203634143 created "2021-10-11" @default.
- W3203634143 creator A5003758687 @default.
- W3203634143 creator A5035227367 @default.
- W3203634143 creator A5045047866 @default.
- W3203634143 creator A5066074825 @default.
- W3203634143 date "2018-09-26" @default.
- W3203634143 modified "2023-09-24" @default.
- W3203634143 doi "https://doi.org/10.28951/rbb.v36i3.286" @default.
- W3203634143 hasPublicationYear "2018" @default.
- W3203634143 type Work @default.
- W3203634143 sameAs 3203634143 @default.
- W3203634143 citedByCount "2" @default.
- W3203634143 countsByYear W32036341432020 @default.
- W3203634143 countsByYear W32036341432021 @default.
- W3203634143 crossrefType "journal-article" @default.
- W3203634143 hasAuthorship W3203634143A5003758687 @default.
- W3203634143 hasAuthorship W3203634143A5035227367 @default.
- W3203634143 hasAuthorship W3203634143A5045047866 @default.
- W3203634143 hasAuthorship W3203634143A5066074825 @default.
- W3203634143 hasBestOaLocation W32036341431 @default.
- W3203634143 hasConcept C185592680 @default.
- W3203634143 hasConceptScore W3203634143C185592680 @default.
- W3203634143 hasIssue "3" @default.
- W3203634143 hasLocation W32036341431 @default.
- W3203634143 hasOpenAccess W3203634143 @default.
- W3203634143 hasPrimaryLocation W32036341431 @default.
- W3203634143 hasRelatedWork W2089004370 @default.
- W3203634143 hasRelatedWork W2265581526 @default.
- W3203634143 hasRelatedWork W2552279841 @default.
- W3203634143 hasRelatedWork W2792122310 @default.
- W3203634143 hasRelatedWork W3015026561 @default.
- W3203634143 hasRelatedWork W3203634143 @default.
- W3203634143 hasRelatedWork W4224238632 @default.
- W3203634143 hasRelatedWork W4286719103 @default.
- W3203634143 hasRelatedWork W974530574 @default.
- W3203634143 hasRelatedWork W2560637633 @default.
- W3203634143 hasVolume "36" @default.
- W3203634143 isParatext "false" @default.
- W3203634143 isRetracted "false" @default.
- W3203634143 magId "3203634143" @default.
- W3203634143 workType "article" @default.