Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/16991
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dc.contributor.authorPalagi, L-
dc.contributor.authorPesyridis, A-
dc.contributor.authorSciubba, E-
dc.contributor.authorTocci, L-
dc.date.accessioned2018-10-15T13:44:44Z-
dc.date.available2018-10-15T13:44:44Z-
dc.date.issued2018-10-13-
dc.identifier.citationPalagi, L., Pesyridis, A., Sciubba, E. and Tocci, L. (2019) 'Machine Learning for the prediction of the dynamic behavior of a small scale ORC system', Energy, 166, pp. 72-82. doi: 10.1016/j.energy.2018.10.059.en_US
dc.identifier.issn0360-5442-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/16991-
dc.description.sponsorshipThis work was funded by the 2016 Scholarship of the Knowledge Center on OrganicRankine Cycle (KC ORC, www.kcorc.org), awarded to Lorenzo Tocci to work on this researchproject with Dr Pesyridis at Brunel University London. Entropea Labs is also acknowledgedfor the economic and technical support provided during the completion of this study.-
dc.description.sponsorship2016 Scholarship of the Knowledge Center on Organic Rankine Cycle (KC ORC, www.kcorc.org)-
dc.format.mediumPrint-Electronic-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectartificial neural networksen_US
dc.subjectORCen_US
dc.subjectdynamic systemen_US
dc.subjectexperimental ORCen_US
dc.titleMachine Learning for the prediction of the dynamic behavior of a small scale ORC systemen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.energy.2018.10.059-
dc.relation.isPartOfEnergy-
pubs.publication-statusPublished-
dc.identifier.eissn1873-6785-
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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