Show simple item record

dc.contributor.authorStander, Tiaan
dc.contributor.authorRens, Johan
dc.date.accessioned2017-02-17T09:56:39Z
dc.date.available2017-02-17T09:56:39Z
dc.date.issued2014
dc.identifier.citationStander, T. & Rens, J. 2014. Quality of supply data mining. IEEE 16th International Conference on Harmonics and Quality of Power (ICHQP), 25-28 May: 44-48. [http://ieeexplore.ieee.org/document/6842887/]en_US
dc.identifier.isbn978-1-4673-6487-4 (Online)
dc.identifier.issn2164-0610 (Online)
dc.identifier.issn1540-6008
dc.identifier.urihttp://hdl.handle.net/10394/20409
dc.identifier.urihttp://dx.doi.org/ 10.1109/ICHQP.2014.6842887
dc.identifier.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6842887
dc.description.abstractExtracting useful network management information from a large volume of QoS data obtained all over a network can be simplified by innovative data mining techniques. The need for QoS expertise is reduced as interactive visualization by brushing and linking of datasets reveals interrelation of parameters. Data contextualization by annotated data can aid the assessment on the global level of compatibility between supply and use conditions. Data dashboards can further simplify the analysis of QoS data by recognizing the network connectivity of different sites, seasonal effects and direction of voltage waveform eventsen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectData dashboardsen_US
dc.subjectQoSen_US
dc.subjectPQen_US
dc.subjectData miningen_US
dc.subjectSQLen_US
dc.subjectQoS reportingen_US
dc.subjectCompliance to compatibilityen_US
dc.subjectNetwork risk managementen_US
dc.subjectInteractive data visualizationen_US
dc.subjectContextualizationen_US
dc.titleQuality of supply data miningen_US
dc.typePresentationen_US
dc.contributor.researchID10200029 - Rens, Abraham Paul Johannes


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record