Comparison of Neural Network and Grammatical Evolution for Time Series Prediction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F13%3APU104589" target="_blank" >RIV/00216305:26210/13:PU104589 - isvavai.cz</a>
Alternative codes found
RIV/62156489:43110/13:00214084
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Comparison of Neural Network and Grammatical Evolution for Time Series Prediction
Original language description
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 modeland setup difficulty.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mendel 2013
ISBN
978-80-214-4755-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
215-220
Publisher name
Neuveden
Place of publication
Brno
Event location
Brno University of Technology
Event date
Jun 26, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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