Multilayer Perceptron Models for Band Diagram Prediction in bi-dimensional Photonic Crystals
| dc.contributor.author | Ferreira, Adriano da Silva | |
| dc.contributor.author | Malheiros Silveira, Gilliard Nardel [UNESP] | |
| dc.contributor.author | Hernandez Figueroa, Hugo Enrique | |
| dc.contributor.author | IEEE | |
| dc.contributor.institution | Universidade Estadual de Campinas (UNICAMP) | |
| dc.contributor.institution | Sao Paulo Fed Inst Educ Sci & Technol IFSP | |
| dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
| dc.date.accessioned | 2019-10-04T11:56:53Z | |
| dc.date.available | 2019-10-04T11:56:53Z | |
| dc.date.issued | 2018-01-01 | |
| dc.description.abstract | We modeled Multilayer Perceptron (MLP) Artificial Neural Network for predicting band diagrams (BD) of bi-dimensional photonic crystals. Datasets for MLP training were created by relating geometric and material properties to BDs of triangular-and square-lattice photonic crystals. We demonstrate that fast-training MLP models are able to estimate accurate BDs and existing photonic band gaps through rapid computations. | en |
| dc.description.affiliation | Univ Estadual Campinas, Sch Elect & Comp Engn FEEC, Campinas, SP, Brazil | |
| dc.description.affiliation | Sao Paulo Fed Inst Educ Sci & Technol IFSP, Hortolandia, Brazil | |
| dc.description.affiliation | Sao Paulo State Univ UNESP, Sao Joao Da Boa Vista, Brazil | |
| dc.description.affiliationUnesp | Sao Paulo State Univ UNESP, Sao Joao Da Boa Vista, Brazil | |
| dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
| dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description.sponsorshipId | CNPq: 312110/2016-2 | |
| dc.description.sponsorshipId | FAPESP: 2015/24517-8 | |
| dc.format.extent | 5 | |
| dc.identifier.citation | 2018 Sbfoton International Optics And Photonics Conference (sbfoton Iopc). New York: Ieee, 5 p., 2018. | |
| dc.identifier.uri | http://hdl.handle.net/11449/184350 | |
| dc.identifier.wos | WOS:000458662800043 | |
| dc.language.iso | eng | |
| dc.publisher | Ieee | |
| dc.relation.ispartof | 2018 Sbfoton International Optics And Photonics Conference (sbfoton Iopc) | |
| dc.rights.accessRights | Acesso aberto | pt |
| dc.source | Web of Science | |
| dc.subject | photonic crystal | |
| dc.subject | photonic band gap | |
| dc.subject | multilayer perceptron | |
| dc.subject | prediction | |
| dc.title | Multilayer Perceptron Models for Band Diagram Prediction in bi-dimensional Photonic Crystals | en |
| dc.type | Trabalho apresentado em evento | pt |
| dcterms.license | http://www.ieee.org/publications_standards/publications/rights/rights_policies.html | |
| dcterms.rightsHolder | Ieee | |
| dspace.entity.type | Publication | |
| relation.isOrgUnitOfPublication | 72ed3d55-d59c-4320-9eee-197fc0095136 | |
| relation.isOrgUnitOfPublication.latestForDiscovery | 72ed3d55-d59c-4320-9eee-197fc0095136 | |
| unesp.campus | Universidade Estadual Paulista (UNESP), Faculdade de Engenharia, São João da Boa Vista | pt |