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

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorMol, Adriano Aguiar-
Autor(es): dc.creatorMartins Filho, Luiz de Siqueira-
Autor(es): dc.creatorSilva, José Demisio Simões da-
Autor(es): dc.creatorRocha, Ronilson-
Data de aceite: dc.date.accessioned2019-11-06T13:34:46Z-
Data de disponibilização: dc.date.available2019-11-06T13:34:46Z-
Data de envio: dc.date.issued2015-05-26-
Data de envio: dc.date.issued2015-05-26-
Data de envio: dc.date.issued2007-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/handle/123456789/5539-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/558567-
Descrição: dc.descriptionThis 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.-
Idioma: dc.languageen-
Direitos: dc.rightsO Periódico Computational Materials Science concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3621890506404.-
Palavras-chave: dc.subjectFaceted gemstones-
Palavras-chave: dc.subjectLapidary design-
Palavras-chave: dc.subjectDesign efficiency-
Palavras-chave: dc.subjectArtificial neural networks-
Título: dc.titleEfficiency parameters estimation in gemstones cut design using artificial neural networks.-
Aparece nas coleções:Repositório Institucional - UFOP

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