Neural Network with Cooperative Switching Units with Application to Time Series Forecasting

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F09%3A00323370" target="_blank" >RIV/67985807:_____/09:00323370 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Neural Network with Cooperative Switching Units with Application to Time Series Forecasting
Original language description
Simple neural networks with switching units are capable to predict seasonal time series with results comparable to common stochastic methods. This paper presents enhanced model of neural network with switching units with aim to improve the forecasting performance of non-stationary time series. The presented model of neural network network is build of neurons with feedback and continuous activation function and it has a two level topology. The paper further describes the application of genetic algorithmsto the optimization of the first level of topology. Finally, the performance of the proposed model was tested on the time series of currency in circulation and two artificial seasonal stochastic processes. Experimental results confirm that the new modeloutperforms the basic one as well as common stochastic methods.
Czech name
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Czech description
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Project
<a href="/en/project/1M0567" target="_blank" >1M0567: Centre for Applied Cybernetics</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
World Congress on Computer Science and Information Engineering
ISBN
978-0-7695-3507-4
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
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Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Los Angeles
Event date
Mar 31, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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