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dc.contributor.authorPotts, Rebecca Lauren
dc.contributor.authorLeontidis, Georgios
dc.date.accessioned2022-11-24T20:41:02Z
dc.date.available2022-11-24T20:41:02Z
dc.date.issued2023-01-23
dc.identifier.citationPotts , R L & Leontidis , G 2023 , ' Attention-Based Deep Learning Methods for Predicting Gas Turbine Emissions ' , Northern Lights Deep Learning Conference 2023 (Extended Abstracts) , Tromso , Norway , 9/01/23 - 13/01/23 .en
dc.identifier.citationconferenceen
dc.identifier.otherPURE: 222474882
dc.identifier.otherPURE UUID: b1961909-3c8a-4562-ad56-caf67e7e4cdb
dc.identifier.urihttps://hdl.handle.net/2164/19602
dc.descriptionThis work was supported by the Engineering and Physical Sciences Research Council [EP/W522089/1].en
dc.format.extent3
dc.language.isoeng
dc.subjectSDG 9 - Industry, Innovation, and Infrastructureen
dc.subjectSDG 7 - Affordable and Clean Energyen
dc.subject2040 Data and Artificial Intelligenceen
dc.subjectArtificial intelligenceen
dc.subjectDeep Learningen
dc.subjectGas Turbinesen
dc.subjectpredicting emissionsen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectEngineering and Physical Sciences Research Council (EPSRC)en
dc.subjectEP/W522089/1en
dc.subject.lccQA75en
dc.titleAttention-Based Deep Learning Methods for Predicting Gas Turbine Emissionsen
dc.typeConference posteren
dc.contributor.institutionUniversity of Aberdeen.Natural & Computing Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Vice Principalsen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Machine Learningen
dc.contributor.institutionUniversity of Aberdeen.Centre for Energy Transitionen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen


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