Learning Regions Identification by Unsupervised Methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F09%3A00009192" target="_blank" >RIV/00216275:25410/09:00009192 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Learning Regions Identification by Unsupervised Methods
Original language description
The paper discusses the importance of knowledge in regional development. The basic notions of learning regions are presented. The input variables are proposed for the modelling of NUTS 2 regions in order to identify learning regions. The identification of the learning regions is realized by unsupervised methods. Data are analyzed by the model merging neural networks and cluster analysis algorithm with the aim of data dimension reduction and, moreover, the model makes it possible to visualize regions ina topological map. The results show on the membership of regions to learning regions.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
3rd Central European Conference in Regional Science - International Conference Proceedings
ISBN
978-80-553-0329-1
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
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Publisher name
Technická univerzita v Košicích
Place of publication
Košice
Event location
Košice, SK
Event date
Oct 9, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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