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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F12%3A86084949%21RIV13-MSM-27240___
rdf:type
n14:Vysledek skos:Concept
dcterms:description
This paper deals with using a K-means clustering which is used for decision what parameter related to weather affects a propagation of radio waves in mobile telecommunication network. There were analysed parameters from a meteorological service as well as the parameters related to Global System of Mobile Communication network. For this purpose, we studied and used theory of data mining. The second part of the paper is focused on the significant weather parameters as results of K-means analyse. Consequently, there have been found some dependencies between weather conditions and receive level using a mathematical tools of correlation analysis via MATLAB. This paper deals with using a K-means clustering which is used for decision what parameter related to weather affects a propagation of radio waves in mobile telecommunication network. There were analysed parameters from a meteorological service as well as the parameters related to Global System of Mobile Communication network. For this purpose, we studied and used theory of data mining. The second part of the paper is focused on the significant weather parameters as results of K-means analyse. Consequently, there have been found some dependencies between weather conditions and receive level using a mathematical tools of correlation analysis via MATLAB.
dcterms:title
K-mean clustering and correlation analysis in recognition of weather impact on radio signal K-mean clustering and correlation analysis in recognition of weather impact on radio signal
skos:prefLabel
K-mean clustering and correlation analysis in recognition of weather impact on radio signal K-mean clustering and correlation analysis in recognition of weather impact on radio signal
skos:notation
RIV/61989100:27240/12:86084949!RIV13-MSM-27240___
n14:predkladatel
n15:orjk%3A27240
n3:aktivita
n12:S
n3:aktivity
S
n3:dodaniDat
n19:2013
n3:domaciTvurceVysledku
n10:5908124 n10:5520762 n10:2457318 n10:2136295 n10:2856859
n3:druhVysledku
n21:D
n3:duvernostUdaju
n11:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
144791
n3:idVysledku
RIV/61989100:27240/12:86084949
n3:jazykVysledku
n18:eng
n3:klicovaSlova
weather; K-means; GSM; data mining; Clustering
n3:klicoveSlovo
n4:Clustering n4:GSM n4:weather n4:data%20mining n4:K-means
n3:kontrolniKodProRIV
[093C7270C980]
n3:mistoKonaniAkce
Praha
n3:mistoVydani
New York
n3:nazevZdroje
TSP 2012 : 35th International Conference on Telecommunications and Signal Processing : July 3-4, 2012, Prague, Czech Republic
n3:obor
n7:JA
n3:pocetDomacichTvurcuVysledku
5
n3:pocetTvurcuVysledku
5
n3:rokUplatneniVysledku
n19:2012
n3:tvurceVysledku
Blaha, Petr Dvorský, Marek Šebesta, Roman Michalek, Libor Skapa, Jan
n3:typAkce
n13:WRD
n3:zahajeniAkce
2012-07-03+02:00
s:numberOfPages
4
n22:doi
10.1109/TSP.2012.6256306
n9:hasPublisher
IEEE
n20:isbn
978-1-4673-1118-2
n5:organizacniJednotka
27240