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Digital Library of the
European Council for Modelling and Simulation |
Title: |
Elliott
Waves Recognition Via Neural Networks |
Authors: |
Martin Kotyrba, Eva Volná, David Bražina, Robert Jarušek |
Published in: |
(2012).ECMS
2012 Proceedings edited by: K. G. Troitzsch, M. Moehring, U. Lotzmann. European
Council for Modeling and Simulation. doi:10.7148/2012 ISBN:
978-0-9564944-4-3 26th
European Conference on Modelling and Simulation, Shaping reality through simulation Koblenz,
Germany, May 29 – June 1 2012 |
Citation
format: |
Kortyrba, M., Volna,
E., Brazina, D., & Jarusek,
R. (2012). Elliott Waves Recognition Via Neural Networks. ECMS 2012
Proceedings edited by: K. G. Troitzsch, M. Moehring, U. Lotzmann
(pp. 361-366). European Council for Modeling and Simulation. doi:10.7148/2012-0361-0366 |
DOI: |
http://dx.doi.org/10.7148/2012-0361-0366 |
Abstract: |
In this paper we introduce our
method that is able to analyze and recognize Elliott waves in time series.
Our method uses an artificial neural network that is adapted by backpropagation. Neural network uses Elliot wave’s
patterns in order to extract them and recognize. Artificial neural networks
are suitable for pattern recognition in time series mainly because of
learning only from examples. There is no need to add additional information
that could bring more confusion than recognition effect. Neural networks are
able to generalize and are resistant to noise. On the other hand, it is
generally not possible to determine exactly what a neural network learned and
it is also hard to estimate possible recognition error. They are ideal
especially when we do not have any other description of the observed series.
This paper also includes experimental results of Elliott waves recognition
carried out with our method. |
Full
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