Irradiance prediction using Echo State Queueing Networks and Differential Polynomial Neural Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F13%3A86087624" target="_blank" >RIV/61989100:27730/13:86087624 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/13:86087624 RIV/61989100:27740/13:86087624
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Irradiance prediction using Echo State Queueing Networks and Differential Polynomial Neural Networks
Original language description
This paper investigates the estimation of a real time-series benchmark: the solar irradiance forcasting. The global solar irradiance is an important variable in the production of renewable energy sources. These variable is very unstable and hard to be predicted. For the prediction, we use two new models for time-seriesmodeling: Echo StateQueueing Networks and Differential polynomial Neural Networks. Both tools have been proven to be efficient for forecasting and time-seriesmodeling. We compare their performances for this particular data set.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2013 International Conference on Intelligent Systems Design and Applications (ISDA 2013) : Universiti Putra Malaysia, Malaysia, 08-10 December, 2013
ISBN
978-1-4799-3516-1
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
261-266
Publisher name
IEEE
Place of publication
New York
Event location
Serdang, Selangor
Event date
Dec 8, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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