Publication detail

Learning Regions Identification by Unsupervised Methods

Authors: Hájková Veronika | Hájek Petr

Year: 2009

Type of publication: článek ve sborníku

Name of source: 3rd Central European Conference in Regional Science - International Conference Proceedings

Publisher name: Technická univerzita v Košiciach

Place: Košice

Page from-to: 1037-1048

Titles:

Language	Name	Abstract	Keywords
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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