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Phytoplankton analysis of portuguese reservoirs: a cluster analysis with R

dc.contributor.authorCorreia, Aldina
dc.contributor.authorLopes, Isabel Cristina
dc.contributor.authorSilva, Eliana Costa e
dc.contributor.authorCabecinha, Edna
dc.date.accessioned2015-04-24T11:37:44Z
dc.date.available2015-04-24T11:37:44Z
dc.date.issued2015
dc.description.abstractIn this work, cluster analysis is applied to a real dataset of biological features of several Portuguese reservoirs. All the statistical analysis is done using R statistical software. Several metrics and methods were explored, as well as the combination of Euclidean metric and the hierarchical Ward method. Although it did not present the best combination in terms of internal and stability validation, it was still a good solution and presented good results in terms of interpretation of the problem at hand.por
dc.identifier.doi10.1063/1.4913053
dc.identifier.isbn978-0-7354-1287-3
dc.identifier.urihttp://hdl.handle.net/10400.22/5831
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherAIP Publishingpor
dc.relation.publisherversionhttp://scitation.aip.org/content/aip/proceeding/aipcp/10.1063/1.4913053por
dc.subjectCluster analysispor
dc.subjectPhytoplanktonpor
dc.titlePhytoplankton analysis of portuguese reservoirs: a cluster analysis with Rpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceRhodes, Greecepor
oaire.citation.endPage840013-2por
oaire.citation.startPage840013-1por
oaire.citation.titleProceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014 (ICNAAM-2014)por
oaire.citation.volume1648por
person.familyNameLopes
person.givenNameIsabel Cristina
person.identifier2277025
person.identifier.ciencia-idBC14-DF88-AEBC
person.identifier.orcid0000-0002-4833-470X
person.identifier.ridL-7458-2017
person.identifier.scopus-author-id36185835200
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication70af5a18-432a-4ef9-862d-c5a79581c255
relation.isAuthorOfPublication.latestForDiscovery70af5a18-432a-4ef9-862d-c5a79581c255

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