Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/115061
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dc.contributor.advisorFigueras Siñol, Francesca-
dc.contributor.authorPallares Guimera, Esther-
dc.date.accessioned2017-09-06T16:44:57Z-
dc.date.available2017-09-06T16:44:57Z-
dc.date.issued2017-01-
dc.identifier.urihttp://hdl.handle.net/2445/115061-
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2017, Tutora: Francesca Figuerascat
dc.description.abstractGaia is an ESA mission that observes about 50 million sources per day. A small part of these detections are considered spurious generated for example by cosmic rays. The main objective of this study is to perform a comparative analysis of several algorithms to automatically detect spurious detections. Successfully identifying these detections is important to prevent them from entering the cross-match stage where they create several problems and degrade resolution performance. We will use appropriate metrics to determine the execution and assess the algorithms. Finally, it will be discussed if any of these data mining algorithms could be a good solution to the spurious detection problem.eng
dc.format.extent5 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengeng
dc.rightscc-by-nc-nd (c) Pallares, 2017-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/-
dc.subject.classificationObservatoris astronòmicscat
dc.subject.classificationAlgorismes computacionalscat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherAstronomical observatorieseng
dc.subject.otherComputer algorithmseng
dc.subject.otherBachelor's thesiseng
dc.titleA comparative analysis of data mining algorithms to mitigate spurious detections in Gaiaeng
dc.typeinfo:eu-repo/semantics/bachelorThesiseng
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesseng
Appears in Collections:Treballs Finals de Grau (TFG) - Física

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