VYUŽITÍ NEURONOVÝCH SÍTÍ V SYSTÉMECH TZB

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

ARTIFICIAL NEURAL NETWORKS UTILIZATION WITHIN BUILDING ENERGY AND ENVIRONMENTAL SYSTEMS

Popis výsledku v původním jazyce

Information technology progress influences all of our life. Modern buildings are significant example of formation of indoor climate conditions including all HVAC systems within a building. As our qualitative requirements increase, grows also importance of building energy performance as well as energy performance of all systems. Along with high efficiency components is significant factor related to systems control. Present status of regulation and control systems allow incorporation of highly sophistic procedures. One of these procedures is utilization of artificial neural networks as computational core of the control system. These artificial neural networks offer possibility of approximation of large scale and complex mathematical models. So much simpler approach in mutual relationships between inputs, parameters and outputs replace original model. Another great advantage lies in learning ability from previous results and supplied data. These possibilities discusses following paper.

Název v anglickém jazyce

ARTIFICIAL NEURAL NETWORKS UTILIZATION WITHIN BUILDING ENERGY AND ENVIRONMENTAL SYSTEMS

Popis výsledku anglicky

Information technology progress influences all of our life. Modern buildings are significant example of formation of indoor climate conditions including all HVAC systems within a building. As our qualitative requirements increase, grows also importance of building energy performance as well as energy performance of all systems. Along with high efficiency components is significant factor related to systems control. Present status of regulation and control systems allow incorporation of highly sophistic procedures. One of these procedures is utilization of artificial neural networks as computational core of the control system. These artificial neural networks offer possibility of approximation of large scale and complex mathematical models. So much simpler approach in mutual relationships between inputs, parameters and outputs replace original model. Another great advantage lies in learning ability from previous results and supplied data. These possibilities discusses following paper.

Druh

D - Stať ve sborníku

CEP obor

JE - Nejaderná energetika, spotřeba a užití energie

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

XII Mezinárodní vědecká konference Technická zařízení staveb a energie budov

ISBN

978-80-7204-629-4

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

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Název nakladatele

Akademické nakladatelství CERM

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

20. 4. 2009

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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