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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/1M0567" target="_blank" >1M0567: Centrum aplikované kybernetiky</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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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Počet stran výsledku

7

Strana od-do

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Název nakladatele

IEEE Computer Society

Místo vydání

Los Alamitos

Místo konání akce

Los Angeles

Datum konání akce

31. 3. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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