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Parametric study of the analog ensembles algorithm with clustering methods for hindcasting with multistations

dc.contributor.authorAraújo, Leonardo Oliveira
dc.contributor.authorBalsa, Carlos
dc.contributor.authorRodrigues, Carlos Veiga
dc.contributor.authorRufino, José
dc.date.accessioned2022-01-13T14:40:37Z
dc.date.available2022-01-13T14:40:37Z
dc.date.issued2021
dc.description.abstractWeather prediction for locations without or scarce meteorological data available can be attempted by taking meteorological datasets from nearby stations. This hindcasting problem can be successfully solved using the Analog Ensemble (AnEn) method. This paper presents a parametric analysis of the AnEn method, and two variations (based on K-means and fuzzy C-means clustering methods), when used to search for analog ensembles in a historical dataset. The study allowed to identify the parameter combinations that yield the best prediction accuracy, improving 13% on the systematic error and 5% on the random error of the previous results obtained with the same dataset. In addition, important performance gains were achieved at the computational level.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAraújo, Leonardo; Balsa, Carlos; Rodrigues, C. Veiga; Rufino, José (2021). Parametric study of the analog ensembles algorithm with clustering methods for hindcasting with multistations. In World Conference on Information Systems and Technologies, WorldCIST 2021. p. 544-559. ISBN 978-3-030-72650-8
dc.identifier.doi10.1007/978-3-030-72651-5_52pt_PT
dc.identifier.isbn978-3-030-72650-8
dc.identifier.urihttp://hdl.handle.net/10198/24627
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAnalog ensemblespt_PT
dc.subjectClusteringpt_PT
dc.subjectTime seriespt_PT
dc.subjectMeteorological datapt_PT
dc.subjectHindcastingpt_PT
dc.titleParametric study of the analog ensembles algorithm with clustering methods for hindcasting with multistationspt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.endPage559pt_PT
oaire.citation.startPage544pt_PT
oaire.citation.volume1366pt_PT
person.familyNameBalsa
person.familyNameRufino
person.givenNameCarlos
person.givenNameJosé
person.identifier1721518
person.identifier.ciencia-idDE1E-2F7A-AAB1
person.identifier.ciencia-idC414-F47F-6323
person.identifier.orcid0000-0003-2431-8665
person.identifier.orcid0000-0002-1344-8264
person.identifier.ridM-8735-2013
person.identifier.scopus-author-id23391719100
person.identifier.scopus-author-id55947199100
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationd0e5ccff-9696-4f4f-9567-8d698a6bf17d
relation.isAuthorOfPublication1e24d2ce-a354-442a-bef8-eebadd94b385
relation.isAuthorOfPublication.latestForDiscoveryd0e5ccff-9696-4f4f-9567-8d698a6bf17d

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