Design of a Model for Heat Demand Prediction Using the Neural Network Synthesis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F12%3A43869055" target="_blank" >RIV/70883521:28140/12:43869055 - 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

Design of a Model for Heat Demand Prediction Using the Neural Network Synthesis

Popis výsledku v původním jazyce

This paper deals with design of a model for short-term heat demand forecasting. Forecast of this heat demand course is significant for short-term planning of heat production and it is most important for technical and economic consideration. In this paperwe 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). Forecast of socialcomponent is realized by means of Box-Jenkins methodology. For inclusion of outdoor temperature influence in calculation of prediction of heat demand is used the 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 used for optimal finding of the expression.

Název v anglickém jazyce

Design of a Model for Heat Demand Prediction Using the Neural Network Synthesis

Popis výsledku anglicky

This paper deals with design of a model for short-term heat demand forecasting. Forecast of this heat demand course is significant for short-term planning of heat production and it is most important for technical and economic consideration. In this paperwe 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). Forecast of socialcomponent is realized by means of Box-Jenkins methodology. For inclusion of outdoor temperature influence in calculation of prediction of heat demand is used the 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 used for optimal finding of the expression.

Druh

D - Stať ve sborníku

CEP obor

JE - Nejaderná energetika, spotřeba a užití energie

OECD FORD obor

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Projekt

<a href="/cs/project/ED2.1.00%2F03.0089" target="_blank" >ED2.1.00/03.0089: Centrum bezpečnostních, informačních a pokročilých technologií (CEBIA-Tech)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 6th International Conference on Applied Mathematics, Simulation, Modelling

ISBN

978-1-61804-076-3

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

86-91

Název nakladatele

WSEAS Press (GR)

Místo vydání

Athens

Místo konání akce

Athens

Datum konání akce

7. 3. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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