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

Detalhes bibliográficos
Autor(a) principal: Mol, Adriano Aguiar
Data de Publicação: 2007
Outros Autores: Martins Filho, Luiz de Siqueira, Silva, José Demisio Simões da, Rocha, Ronilson
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFOP
Texto Completo: http://www.repositorio.ufop.br/handle/123456789/5539
https://doi.org/10.1016/j.commatsci.2006.05.012
Resumo: This 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.
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spelling Efficiency parameters estimation in gemstones cut design using artificial neural networks.Faceted gemstonesLapidary designDesign efficiencyArtificial neural networksThis 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.2015-05-26T18:35:28Z2015-05-26T18:35:28Z2007info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfMOL, 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. 2015.0927-0256http://www.repositorio.ufop.br/handle/123456789/5539https://doi.org/10.1016/j.commatsci.2006.05.012O periódico Computational Materials Science concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3621890506404.info:eu-repo/semantics/openAccessMol, Adriano AguiarMartins Filho, Luiz de SiqueiraSilva, José Demisio Simões daRocha, Ronilsonengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOP2019-07-26T17:47:02Zoai:repositorio.ufop.br:123456789/5539Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332019-07-26T17:47:02Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false
dc.title.none.fl_str_mv Efficiency parameters estimation in gemstones cut design using artificial neural networks.
title Efficiency parameters estimation in gemstones cut design using artificial neural networks.
spellingShingle Efficiency parameters estimation in gemstones cut design using artificial neural networks.
Mol, Adriano Aguiar
Faceted gemstones
Lapidary design
Design efficiency
Artificial neural networks
title_short Efficiency parameters estimation in gemstones cut design using artificial neural networks.
title_full Efficiency parameters estimation in gemstones cut design using artificial neural networks.
title_fullStr Efficiency parameters estimation in gemstones cut design using artificial neural networks.
title_full_unstemmed Efficiency parameters estimation in gemstones cut design using artificial neural networks.
title_sort Efficiency parameters estimation in gemstones cut design using artificial neural networks.
author Mol, Adriano Aguiar
author_facet Mol, Adriano Aguiar
Martins Filho, Luiz de Siqueira
Silva, José Demisio Simões da
Rocha, Ronilson
author_role author
author2 Martins Filho, Luiz de Siqueira
Silva, José Demisio Simões da
Rocha, Ronilson
author2_role author
author
author
dc.contributor.author.fl_str_mv Mol, Adriano Aguiar
Martins Filho, Luiz de Siqueira
Silva, José Demisio Simões da
Rocha, Ronilson
dc.subject.por.fl_str_mv Faceted gemstones
Lapidary design
Design efficiency
Artificial neural networks
topic Faceted gemstones
Lapidary design
Design efficiency
Artificial neural networks
description This 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.
publishDate 2007
dc.date.none.fl_str_mv 2007
2015-05-26T18:35:28Z
2015-05-26T18:35:28Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv MOL, 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.
0927-0256
http://www.repositorio.ufop.br/handle/123456789/5539
https://doi.org/10.1016/j.commatsci.2006.05.012
identifier_str_mv MOL, 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.
0927-0256
url http://www.repositorio.ufop.br/handle/123456789/5539
https://doi.org/10.1016/j.commatsci.2006.05.012
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFOP
instname:Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
instname_str Universidade Federal de Ouro Preto (UFOP)
instacron_str UFOP
institution UFOP
reponame_str Repositório Institucional da UFOP
collection Repositório Institucional da UFOP
repository.name.fl_str_mv Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)
repository.mail.fl_str_mv repositorio@ufop.edu.br
_version_ 1813002836101824512

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