Artificial intelligence in industrial systems

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dc.creatorReinaldo Martinez Palhares
dc.creatorYuan Yuan
dc.creatorQi Wang
dc.date.accessioned2025-05-15T14:13:23Z
dc.date.accessioned2025-09-09T01:25:18Z
dc.date.available2025-05-15T14:13:23Z
dc.date.issued2019
dc.identifier.doihttps://doi.org/10.1109/TIE.2019.2916709
dc.identifier.issn0278-0046
dc.identifier.urihttps://hdl.handle.net/1843/82301
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofIEEE Transactions on industrial electronics
dc.rightsAcesso Restrito
dc.subjectCiência da Computação
dc.subjectEngenharia Elétrica
dc.subject.otherInteligência Artificial
dc.subject.otherInteligência Computacional
dc.subject.otherIndústria 4.0
dc.subject.otherControle
dc.subject.otherControle de Processos
dc.subject.otherSistemas Industrias Complexos
dc.titleArtificial intelligence in industrial systems
dc.typeArtigo de periódico
local.citation.epage9640
local.citation.spage9636
local.citation.volume66
local.description.resumoArtificial intelligence has played an important role in industrial community over the last decades. Benefited from the recent progress in data acquisition and high-performance computing, artificial intelligence technology has gained a great development, and plenty of industrial products have been built with intelligent abilities. Artificial intelligence techniques improve the performance of industrial systems, whereas the practical applications in industry inspire the theoretical advances of artificial intelligence in turn. Although artificial intelligence has shown great success in solving real-world problems, there is still room for improvement due to the complexity of industrial tasks.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/8784425

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