Publikace detail

Learning Regions Identification by Unsupervised Methods

Autoři: Hájková Veronika | Hájek Petr

Rok: 2009

Druh publikace: článek ve sborníku

Název zdroje: 3rd Central European Conference in Regional Science - International Conference Proceedings

Název nakladatele: Technická univerzita v Košiciach

Místo vydání: Košice

Strana od-do: 1037-1048

Tituly:

Jazyk	Název	Abstrakt	Klíčová slova
cze
eng	Learning Regions Identification by Unsupervised Methods	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 in a topological map. The results show on the membership of regions to learning regions.	Learning regions;Identification;Neural networks

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