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Analysis and Recognition of Standards in Intelligent Hybrid Systems using Natural Computing

dc.contributor.authorLourenço, Rodrigo Francisco Borges [UNESP]
dc.contributor.authorOuta, Roberto
dc.contributor.authorChavarette, Fábio Roberto [UNESP]
dc.contributor.authorGonçalves, Aparecido Carlos [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionFaculty of Technology of Araçatuba
dc.date.accessioned2022-04-29T08:30:50Z
dc.date.available2022-04-29T08:30:50Z
dc.date.issued2021-01-01
dc.description.abstractAbstract. This work shows the application of one of the techniques of bioengineering, the perceptron network in the detection of system failures, and also allows the use of the perceptron network technique in choosing the location of the best sensor to be used in the dynamic system. The application of the perceptron network was adopted because it is considered the best binary linear classifier. This work is considered multidisciplinary and difficult to develop. The final result demonstrates a severe application of pre-processing and processing, until the classification and grouping of signals in the two phases of the work. Through the results found, this work can be considered successful and can be applied in several areas of engineering forstructural analysis.en
dc.description.affiliationUNESP - Univ. Estadual Paulista Faculty of Engineering of Ilha Solteira Department of Mechanical Engineering
dc.description.affiliationFaculty of Technology of Araçatuba Department of Biofuels, Av. Prestes Maia, 1764 - Ipanema
dc.description.affiliationUNESP - Instituto de Química Departamento de Engenharia Física e Matemática, Rua Prof. Francisco Degni, 55
dc.description.affiliationUnespUNESP - Univ. Estadual Paulista Faculty of Engineering of Ilha Solteira Department of Mechanical Engineering
dc.description.affiliationUnespUNESP - Instituto de Química Departamento de Engenharia Física e Matemática, Rua Prof. Francisco Degni, 55
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdFAPESP: 2019/10515-4
dc.description.sponsorshipIdCNPq: 312972/2019-9
dc.format.extent1764-1773
dc.identifierhttp://dx.doi.org/10.22055/jacm.2021.37798.3089
dc.identifier.citationJournal of Applied and Computational Mechanics, v. 7, n. 3, p. 1764-1773, 2021.
dc.identifier.doi10.22055/jacm.2021.37798.3089
dc.identifier.issn2383-4536
dc.identifier.scopus2-s2.0-85110654960
dc.identifier.urihttp://hdl.handle.net/11449/229176
dc.language.isoeng
dc.relation.ispartofJournal of Applied and Computational Mechanics
dc.sourceScopus
dc.subjecthybrid system
dc.subjectnatural computing
dc.subjectperceptron network
dc.subjectpredictive system
dc.subjectVibration
dc.titleAnalysis and Recognition of Standards in Intelligent Hybrid Systems using Natural Computingen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0002-7772-6438[1]
unesp.author.orcid0000-0002-8649-1722[2]
unesp.author.orcid0000-0002-1203-7586[3]
unesp.author.orcid0000-0001-5376-3392[4]
unesp.departmentEngenharia Mecânica - FEISpt

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