Power Demand Daily Predictions using the Combined Differential Polynomial Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F14%3A86090330" target="_blank" >RIV/61989100:27740/14:86090330 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-08156-4_8#page-1" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-08156-4_8#page-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-08156-4_8" target="_blank" >10.1007/978-3-319-08156-4_8</a>
Alternative languages
Result language
angličtina
Original language name
Power Demand Daily Predictions using the Combined Differential Polynomial Network
Original language description
Power demand prediction is important for the economically efficient operation and effective control of power systems and enables to plan the load of generating unit. 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 capacity preparation 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. Cooperation on the electricity grid requires from all providers to foresee the load within a sufficient accuracy. 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 ordinary differential equation, describing 1-paramet
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
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
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Soft Computing. Volume 303
ISBN
978-3-319-08155-7
ISSN
1615-3871
e-ISSN
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Number of pages
10
Pages from-to
73-82
Publisher name
Springer Verlag
Place of publication
London
Event location
Ostrava
Event date
Jun 23, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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