All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Using the self-organizing map for world economic state classificiation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F04%3A00009577" target="_blank" >RIV/61989100:27510/04:00009577 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Using the self-organizing map for world economic state classificiation

  • Original language description

    This paper deals with features and behaviour of Self-Organizing Map (denoted also SOM), also known as Kohonen neural net, in specify economic application. The goal of this paper is to enquire the behaviour of the Kohonen neural net and its using for world economic cluster analyses. SOM differs from classical neural nets based on perceptron in many ways. SOM is used for cluster analyses by comparing initial data vectors. The output of the Kohonen neural net is a map, which shows founded clusters. SOM wasused for world economic classification tries to find an economical position of Czech republic in world benchmark. The initial data vectors contain economic and other outside-economic information such as aircraft departures, surface area, mortality, telephone lines etc. The experiment shows that Czech republic belongs between advanced states together with other central European countries and is situated on the border of the most advanced European Union, Canada and USA and other advanced

  • Czech name

    Světová ekonomická klasifikace s využitím samoorganizujících neuronových sítí

  • Czech description

    V moderní ekonomii se objevují nové trendy, které je zapotřebí zkoumat a analyzovat. S těmito trendy se rozvijí také nástroje pro jejich odbornou a adekvátní analýzu. Jedním z nových nástrojů, který lze pro potřeby ekonomické analýzy uplatnit, je využitíumělých neuronových sítí, sítí Kohonenova typu (také označované jako SOM - Self-Organizing Map). Aplikace sítí typu SOM je provedena na reálných datech států světa za rok 2001 s cílem provést klasifikací podle vybraných kritérií.

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    AH - Economics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2004

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    The 4th annual of international conference IMEA 2004

  • ISBN

    80-7194-679-6

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    35-42

  • Publisher name

    Universita Pardubice

  • Place of publication

    Pardubice

  • Event location

    Pardubice

  • Event date

    May 20, 2004

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article