Comparison of artificial neural networks using prediction benchmarking

Authors:
David Samek;David Manas
Affiliations:
Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, Zlin, Czech Republic;Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, Zlin, Czech Republic
Venue:
ACMOS'11 Proceedings of the 13th WSEAS international conference on Automatic control, modelling & simulation
Year:
2011

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Abstract

Artificial neural networks are commonly used for prediction of various time series, linear and nonlinear systems. Nevertheless, the choice of proper type of artificial neural networks is difficult task, because each class of artificial neural networks has different features and abilities. Aim of this paper is to compare and benchmark four typical categories of artificial neural networks in artificial time series prediction and provide suggestions for this kind of applications.