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Description
  • The article offers detailed computational algorithm used in this type of neural networks, extends their applications to fit and predict the data of economic time series, conducts experiments and indicates the gain of granular neural networks, specifically conducting experimentation using the classical (statistical) or econometric methods and conventional/soft RBF neural networks. Results are analysed and opportunities for future research are suggested.
  • The article offers detailed computational algorithm used in this type of neural networks, extends their applications to fit and predict the data of economic time series, conducts experiments and indicates the gain of granular neural networks, specifically conducting experimentation using the classical (statistical) or econometric methods and conventional/soft RBF neural networks. Results are analysed and opportunities for future research are suggested. (en)
  • Článek poskytuje detailní výpočtový algoritmus navrhnutý pro aproximaci a predikci časových řad prostřednictvím granulační RBF sítě. Je poskytnutá popsaná aplikace aproximace a predikce sítě na ekonomické časové řade. Současně je identifikován přínos vyvinuté metody oproti klasický statistickým, ekonometrickým modelům a modelům založeným a klasických (perceptronových) sítích. V závěru je načrtnut možný směr dalšího výzkumu v této oblasti. (cs)
Title
  • Approximation and Prediction of Wages Based on Granular Neural Network
  • Approximation and Prediction of Wages Based on Granular Neural Network (en)
  • Aproximace a predikce mezd založené na granulární euronové sítí (cs)
skos:prefLabel
  • Approximation and Prediction of Wages Based on Granular Neural Network
  • Approximation and Prediction of Wages Based on Granular Neural Network (en)
  • Aproximace a predikce mezd založené na granulární euronové sítí (cs)
skos:notation
  • RIV/47813059:19240/09:#0002222!RIV09-GA0-19240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA402/08/0022)
http://linked.open...iv/cisloPeriodika
  • 2008
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
  • 303923
http://linked.open...ai/riv/idVysledku
  • RIV/47813059:19240/09:#0002222
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Probabilistic time-series; Classic and soft RBF network; Cloud models; Granular computing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CN - Čínská lidová republika
http://linked.open...ontrolniKodProRIV
  • [451305095A0D]
http://linked.open...i/riv/nazevZdroje
  • Rough Sets and Knowledge Technology. Third International Conference, RSKT 2008, Chengdu, China, May 2008, Proceedings
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • LNAI 5009
http://linked.open...iv/tvurceVysledku
  • Marček, Dušan
  • Marček, Milan
issn
  • 0302-9743
number of pages
http://localhost/t...ganizacniJednotka
  • 19240
is http://linked.open...avai/riv/vysledek of
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