Efficiency parameters estimation in gemstones cut design using artificial neural networks.

dc.contributor.authorMol, Adriano Aguiar
dc.contributor.authorMartins Filho, Luiz de Siqueira
dc.contributor.authorSilva, José Demisio Simões da
dc.contributor.authorRocha, Ronilson
dc.date.accessioned2015-05-26T18:35:28Z
dc.date.available2015-05-26T18:35:28Z
dc.date.issued2007
dc.description.abstractThis paper deals with the problem of estimating cut results for faceted gemstones. The proposed approach applies artificial neural networks for a faceted gemstones analysis tool that could be further developed for incorporation in a computer-aided-design (CAD) context. Basic concepts concerning gemstone processing are introduced and the design of computational tools using neural networks is discussed. The model presented proposes two criteria to assess the efficiency of lapidary designs for rock crystal quartz: brilliance and yield. Closing the article, 62 different lapidary models were used to train and test the neural network tool.pt_BR
dc.identifier.citationMOL, A. A. et al. Efficiency parameters estimation in gemstones cut design using artificial neural networks. Computational Materials Science, v. 38, p. 727-736, 2007. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0927025606001625>. Acesso em: 09 abr. 2015.pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.commatsci.2006.05.012
dc.identifier.issn0927-0256
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/5539
dc.language.isoen_USpt_BR
dc.rights.licenseO periódico Computational Materials Science concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3621890506404.pt_BR
dc.subjectFaceted gemstonespt_BR
dc.subjectLapidary designpt_BR
dc.subjectDesign efficiencypt_BR
dc.subjectArtificial neural networkspt_BR
dc.titleEfficiency parameters estimation in gemstones cut design using artificial neural networks.pt_BR
dc.typeArtigo publicado em periodicopt_BR
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
ARTIGO_EfficiencyParameterEstimation.pdf
Tamanho:
751.61 KB
Formato:
Adobe Portable Document Format
Licença do Pacote
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
license.txt
Tamanho:
2.57 KB
Formato:
Item-specific license agreed upon to submission
Descrição: