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LÝSEK, J. ŠŤASTNÝ, J. MOTYČKA, A.
Original Title
Comparison of Neural Network and Grammatical Evolution for Time Series Prediction
Type
conference paper
Language
English
Original Abstract
In this contribution we present a comparison of a neural network with an agent created by grammatical evolution for time series prediction problem. We use the back-propagation algorithm to train the neural network for predicting future value of a time series. To evolve prediction agents we use grammatical evolution with backwards processing and equalization operator. Finally the results of both methods are compared by their ability to predict time series values, by time needed to create prediction model and setup difficulty.
Keywords
neural network, grammatical evolution, learning, prediction
Key words in English
Authors
LÝSEK, J.; ŠŤASTNÝ, J.; MOTYČKA, A.
RIV year
2013
Released
26. 6. 2013
Location
Brno
ISBN
978-80-214-4755-4
Book
Mendel 2013
Pages from
215
Pages to
220
Pages count
6
BibTex
@inproceedings{BUT100945, author="Jiří {Lýsek} and Jiří {Šťastný} and Arnošt {Motyčka}", title="Comparison of Neural Network and Grammatical Evolution for Time Series Prediction", booktitle="Mendel 2013", year="2013", pages="215--220", address="Brno", isbn="978-80-214-4755-4" }