Location Aware Analytics In The Context Of Mobile Network Performance Optimization

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but.event.date25.04.2019cs
but.event.titleStudent EEICT 2019cs
dc.contributor.authorUrbanová, Lucie
dc.date.accessioned2020-04-16T07:19:30Z
dc.date.available2020-04-16T07:19:30Z
dc.date.issued2019cs
dc.description.abstractThe goal of this paper is to develop an estimation tool capable of predicting location aware network parameters, based on their previous field measurements and to perform a set of additional measurements to verify the accuracy of the tool. Additionally, the paper evaluates a number of regression methods in terms of their prediction accuracy, complexity and the amount of input data needed to create a prediction map of valid results.en
dc.formattextcs
dc.format.extent216-219cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 25st Conference STUDENT EEICT 2019. s. 216-219. ISBN 978-80-214-5735-5cs
dc.identifier.isbn978-80-214-5735-5
dc.identifier.urihttp://hdl.handle.net/11012/186656
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 25st Conference STUDENT EEICT 2019en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectEstimation toolen
dc.subjectGPRen
dc.subjectIDWen
dc.subjectRandom Foresten
dc.subjectRegressionen
dc.titleLocation Aware Analytics In The Context Of Mobile Network Performance Optimizationen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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