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Description
  • Cílem článku je analýza výsledků vybraných shlukovacích metod při klasifikací obcí. V prvním kroku byly využity nehierarchické shlukovací metody s proměnným počtem shluků. Jako alternatnivní přístup ke shlukování byly zde použity i Kohonenovy mapy. V další části byly využity nehierarchické shlukovací metody s pevným počtem shluků.Výsledky shlukování byly analyzovány. Výsledky shlukování a následné klasifikace obcí byly použity ke tvorbě predikčního modelu, který je určen pro potřeby veřejné správy k podpoře rozhodování o financování autobusových linek. (cs)
  • The goal of this paper is the result analysis of chosen cluster methods by the classification of municipalities. A nonhierarchical cluster method with a variable number of clusters is used for the determination of a convenient number of clusters. A Kohonen map is chosen as an alternative approach to standard cluster methods. Nonhierarchical cluster methods with the fixed number of clusters are used for the classification of municipalities, too. The results of methods are analyzed. The classification of municipalities is the starting basis for the creation of a prediction model (PM). The PM is determined for the employees of the Regional Authority to support their decision making by financing of the subsidized bus connection lines.
  • The goal of this paper is the result analysis of chosen cluster methods by the classification of municipalities. A nonhierarchical cluster method with a variable number of clusters is used for the determination of a convenient number of clusters. A Kohonen map is chosen as an alternative approach to standard cluster methods. Nonhierarchical cluster methods with the fixed number of clusters are used for the classification of municipalities, too. The results of methods are analyzed. The classification of municipalities is the starting basis for the creation of a prediction model (PM). The PM is determined for the employees of the Regional Authority to support their decision making by financing of the subsidized bus connection lines. (en)
Title
  • The Result Analysis of the Cluster Methods by the Classification
  • The Result Analysis of the Cluster Methods by the Classification (en)
  • Analýza výsledků metod shlukové analýzy při klasifikaci obcí (cs)
skos:prefLabel
  • The Result Analysis of the Cluster Methods by the Classification
  • The Result Analysis of the Cluster Methods by the Classification (en)
  • Analýza výsledků metod shlukové analýzy při klasifikaci obcí (cs)
skos:notation
  • RIV/00216275:25410/06:00005641!RIV08-MSM-25410___
http://linked.open.../vavai/riv/strany
  • 406-410
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 497431
http://linked.open...ai/riv/idVysledku
  • RIV/00216275:25410/06:00005641
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • cluster analysis; cluster method; neural nets; clustering; municipalities (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [3EA3F14DF7FB]
http://linked.open...v/mistoKonaniAkce
  • Madrid, Spein
http://linked.open...i/riv/mistoVydani
  • Atény
http://linked.open...i/riv/nazevZdroje
  • Preoceedings of the 5th WSEAS International Conferences on Artificial Intelligence, Knowledge Engineering nad Data Bases (AIKED'06)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kašparová, Miloslava
  • Petr, Pavel
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • WSEAS Press
https://schema.org/isbn
  • 960-8457-41-6
http://localhost/t...ganizacniJednotka
  • 25410
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