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Usage of the evolutionary designed neural network for heat demand forecast

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dc.title Usage of the evolutionary designed neural network for heat demand forecast en
dc.contributor.author Chramcov, Bronislav
dc.contributor.author Vařacha, Pavel
dc.relation.ispartof Nostradamus: Modern Methods of Prediction, Modeling and Analysis of Nonlinear Systems
dc.identifier.issn 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 2194-5365 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-642-33226-5
dc.identifier.isbn 978-3-642-33227-2
dc.date.issued 2013
utb.relation.volume 192
dc.citation.spage 103
dc.citation.epage 112
dc.event.title Nostradamus Conference
dc.event.location Ostrava
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2012-09
dc.event.edate 2012-09
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer-Verlag Berlin en
dc.identifier.doi 10.1007/978-3-642-33227-2_13
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-642-33227-2_13
dc.description.abstract This paper highlights the problem of forecast model design for time series of heat demand. We propose the forecast model of heat demand based on the assumption that the course of heat demand can be described sufficiently well as a function of the outdoor temperature and the weather independent component (social components). Time of the day affects the social components. Forecast of social component is realized by means of Box-Jenkins methodology. The weather dependent component is modeled as a heating characteristic (function that describes the temperature-dependent part of heat consumption). The principal aim is to derive an explicit expression for the heating characteristics. The Neural Network Synthesis is successfully applied here to find this expression. An experiment described in the paper was realized on real life data. We have studied half-hourly heat demand data, covering four month period in concrete district heating system (DHS) from Most agglomeration and heating plant situated in Komorany, Czech Republic. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003137
utb.identifier.obdid 43869278
utb.identifier.scopus 2-s2.0-84874633380
utb.identifier.wok 000313767300013
utb.source d-wok
dc.date.accessioned 2013-02-24T06:51:47Z
dc.date.available 2013-02-24T06:51:47Z
utb.contributor.internalauthor Chramcov, Bronislav
utb.contributor.internalauthor Vařacha, Pavel
utb.fulltext.affiliation B. Chramcov and P. Vařacha Tomas Bata University in Zlin, Faculty of Applied Informatics, nam. T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {chramcov,varacha}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported in part by European Regional Development Fund within the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.
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