Publication:
Artificial Intelligence Application in Power Generation Industry: Initial considerations

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dc.citedby2
dc.contributor.authorIsmail R.I.B.en_US
dc.contributor.authorIsmail Alnaimi F.B.en_US
dc.contributor.authorAl-Qrimli H.F.en_US
dc.contributor.authorid57189236796en_US
dc.contributor.authorid58027086700en_US
dc.contributor.authorid30367473200en_US
dc.date.accessioned2023-05-29T06:12:16Z
dc.date.available2023-05-29T06:12:16Z
dc.date.issued2016
dc.descriptionArtificial intelligence; Competition; Condition monitoring; Genetic algorithms; Iterative methods; Neural networks; Problem solving; Fault detection and diagnosis; Faults detection; Intelligent condition monitoring; Mitigation measures; Nonlinear iterations; Plant operations; Power generation industries; Problem-solving abilities; Fault detection; artificial intelligence; artificial neural network; competitiveness; genetic algorithm; industrial technology; monitoring system; power generation; power planten_US
dc.description.abstractWith increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo12007
dc.identifier.doi10.1088/1755-1315/32/1/012007
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84966549032
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84966549032&doi=10.1088%2f1755-1315%2f32%2f1%2f012007&partnerID=40&md5=7592f2a0c9f003f54635c55af8dd9c3d
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22790
dc.identifier.volume32
dc.publisherInstitute of Physics Publishingen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleIOP Conference Series: Earth and Environmental Science
dc.titleArtificial Intelligence Application in Power Generation Industry: Initial considerationsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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