Short-term Power Demand Forecasting using the Differential Polynomial Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F15%3A86090324" target="_blank" >RIV/61989100:27740/15:86090324 - isvavai.cz</a>
Result on the web
<a href="http://www.tandfonline.com/eprint/QI5qIq6CaFEFGT4bkx2h/full" target="_blank" >http://www.tandfonline.com/eprint/QI5qIq6CaFEFGT4bkx2h/full</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/18756891.2015.1001952" target="_blank" >10.1080/18756891.2015.1001952</a>
Alternative languages
Result language
angličtina
Original language name
Short-term Power Demand Forecasting using the Differential Polynomial Neural Network
Original language description
Power demand forecasting is important for economically efficient operation and effective control of power systems and enables to plan the load of generating unit. The purpose of the short-term electricity demand forecasting is to forecast in advance thesystem load, represented by the sum of all consumers load at the same time. A precise load forecasting is required to avoid high generation cost and the spinning reserve capacity. Under-prediction of the demands leads to an insufficient reserve capacitypreparation and can threaten the system stability, on the other hand, over-prediction leads to an unnecessarily large reserve that leads to a high cost preparations. Differential polynomial neural network is a new neural network type, which forms and resolves an unknown general partial differential equation of an approximation of a searched function, described by data observations. It generates convergent sum series of relative polynomial derivative terms which can substitute for the ord
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
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)
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Computational Intelligence Systems
ISSN
1875-6891
e-ISSN
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Volume of the periodical
Vol. 8
Issue of the periodical within the volume
No. 2 (2015)
Country of publishing house
FR - FRANCE
Number of pages
10
Pages from-to
297-306
UT code for WoS article
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EID of the result in the Scopus database
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