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A comparative study on machine learning algorithms for indoor positioning

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dc.contributor.authorGünal, Serkan
dc.contributor.authorGülin Elibol
dc.contributor.authorSerkan Günal
dc.contributor.authorUğur Yayan
dc.contributor.orcid0000-0002-8013-6922
dc.contributor.orcid0000-0002-6626-9649
dc.contributor.orcid0000-0002-9691-1575
dc.contributor.orcid0000-0003-1394-5209
dc.date.accessioned2025-11-13T09:02:57Z
dc.date.issued2015-09-01
dc.identifier.doihttps://doi.org/10.1109/inista.2015.7276725
dc.identifier.openalexW1637458466
dc.identifier.urihttps://hdl.handle.net/11421/309
dc.identifier.urihttps://doi.org/10.1109/inista.2015.7276725
dc.language.isoen
dc.rightsrestrictedAccess
dc.subjectRSS
dc.subjectIndoor positioning system
dc.subjectComputer science
dc.subjectAdaBoost
dc.subjectArtificial intelligence
dc.subjectAlgorithm
dc.subjectSignal strength
dc.subjectMachine learning
dc.subjectClassifier (UML)
dc.subjectPositioning system
dc.subjectDecision tree
dc.subjectHybrid positioning system
dc.subjectk-nearest neighbors algorithm
dc.subjectStatistical classification
dc.subjectComputation
dc.subjectWireless
dc.subjectMathematics
dc.subjectPoint (geometry)
dc.subjectAccelerometer
dc.subjectTelecommunications
dc.titleA comparative study on machine learning algorithms for indoor positioning
dc.typeArticle
dspace.entity.typePublication
local.authorid.openalexA5003391938

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