Analysis and Recognition of Standards in Intelligent Hybrid Systems using Natural Computing
dc.contributor.author | Lourenço, Rodrigo Francisco Borges [UNESP] | |
dc.contributor.author | Outa, Roberto | |
dc.contributor.author | Chavarette, Fábio Roberto [UNESP] | |
dc.contributor.author | Gonçalves, Aparecido Carlos [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | Faculty of Technology of Araçatuba | |
dc.date.accessioned | 2022-04-29T08:30:50Z | |
dc.date.available | 2022-04-29T08:30:50Z | |
dc.date.issued | 2021-01-01 | |
dc.description.abstract | Abstract. 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.affiliation | UNESP - Univ. Estadual Paulista Faculty of Engineering of Ilha Solteira Department of Mechanical Engineering | |
dc.description.affiliation | Faculty of Technology of Araçatuba Department of Biofuels, Av. Prestes Maia, 1764 - Ipanema | |
dc.description.affiliation | UNESP - Instituto de Química Departamento de Engenharia Física e Matemática, Rua Prof. Francisco Degni, 55 | |
dc.description.affiliationUnesp | UNESP - Univ. Estadual Paulista Faculty of Engineering of Ilha Solteira Department of Mechanical Engineering | |
dc.description.affiliationUnesp | UNESP - Instituto de Química Departamento de Engenharia Física e Matemática, Rua Prof. Francisco Degni, 55 | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
dc.description.sponsorshipId | FAPESP: 2019/10515-4 | |
dc.description.sponsorshipId | CNPq: 312972/2019-9 | |
dc.format.extent | 1764-1773 | |
dc.identifier | http://dx.doi.org/10.22055/jacm.2021.37798.3089 | |
dc.identifier.citation | Journal of Applied and Computational Mechanics, v. 7, n. 3, p. 1764-1773, 2021. | |
dc.identifier.doi | 10.22055/jacm.2021.37798.3089 | |
dc.identifier.issn | 2383-4536 | |
dc.identifier.scopus | 2-s2.0-85110654960 | |
dc.identifier.uri | http://hdl.handle.net/11449/229176 | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of Applied and Computational Mechanics | |
dc.source | Scopus | |
dc.subject | hybrid system | |
dc.subject | natural computing | |
dc.subject | perceptron network | |
dc.subject | predictive system | |
dc.subject | Vibration | |
dc.title | Analysis and Recognition of Standards in Intelligent Hybrid Systems using Natural Computing | en |
dc.type | Artigo | |
dspace.entity.type | Publication | |
unesp.author.orcid | 0000-0002-7772-6438[1] | |
unesp.author.orcid | 0000-0002-8649-1722[2] | |
unesp.author.orcid | 0000-0002-1203-7586[3] | |
unesp.author.orcid | 0000-0001-5376-3392[4] | |
unesp.department | Engenharia Mecânica - FEIS | pt |