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Evaluation of MCP correlation algorithms applied to wind data series

2024Conference object Open access
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dc.contributor.authorMoreira, A.
dc.contributor.authorRocha, T.
dc.contributor.authorMendonça, J.
dc.contributor.authorPilão, R.
dc.contributor.authorPinto, P.
dc.date.accessioned2024-11-11T15:41:27Z
dc.date.available2024-11-11T15:41:27Z
dc.date.issued2024
dc.description.abstract(Objectives) This work aimed to develop methodologies for analyzing statistical correlations among wind data series using various Measure-Correlate-Predict (MCP) methods, with the goal of selecting the most suitable method for extrapolating long-term data with minimal associated uncertainty. Furthermore, the study intends to investigate how the concurrent period used to build the correlation can affect the performance indicators of MCP methods.pt_PT
dc.description.versionN/Apt_PT
dc.identifier.citationMoreira, A., Rocha, T., Mendonça, J., Pilão, R., & Pinto, P. (2024, Jun. 26-28). Evaluation of MCP correlation algorithms applied to wind data series [Poster presentation]. ICREPQ’24 - 22nd International Conference on Renewable Energies and Power Quality, Bilbao, Spainpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/26384
dc.language.isoengpt_PT
dc.relationCenter for Innovation in Industrial Engineering and Technology
dc.subjectMeasure-Correlate-Predict (MCP) methodspt_PT
dc.subjectCorrelationspt_PT
dc.titleEvaluation of MCP correlation algorithms applied to wind data seriespt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleCenter for Innovation in Industrial Engineering and Technology
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04730%2F2020/PT
oaire.citation.conferencePlaceBilbao, Spainpt_PT
oaire.citation.titleICREPQ’24 - 22nd International Conference on Renewable Energies and Power Qualitypt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNamePilão
person.givenNameRosa Maria
person.identifier.orcid0000-0001-7715-8576
person.identifier.scopus-author-id6506645717
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication15cb918b-4997-4d6a-9296-323b40c4a9a2
relation.isAuthorOfPublication.latestForDiscovery15cb918b-4997-4d6a-9296-323b40c4a9a2
relation.isProjectOfPublicationcdbfce2f-6ff0-4d59-a7c6-96c99d52a570
relation.isProjectOfPublication.latestForDiscoverycdbfce2f-6ff0-4d59-a7c6-96c99d52a570

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