Approximation and prediction of wages based on granular neural network

  • Authors:
  • Milan Marček;Dušan Marček

  • Affiliations:
  • Faculty of Philosophy and Science, Silesian University, Opava, Czech Republic & MEDIS Nitra, Ltd., Nitra-Dražžovce, Slovak Republic;Faculty of Philosophy and Science, Silesian University, Opava, Czech Republic & Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovak Republic

  • Venue:
  • RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
  • Year:
  • 2008

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Abstract

This article offers a detailed computational algorithm used in that type of neural networks, extends their applications to fit and predict the data of wages 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.