SIMULATION OF TECHNOLOGICAL PROCESSES USING HYBRID TECHNIQUE EXPLORING MATHEMATICAL-PHYSICAL MODELS AND ARTIFICIAL NEURAL NETWORKS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F11%3A86081266" target="_blank" >RIV/61989100:27360/11:86081266 - 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

SIMULATION OF TECHNOLOGICAL PROCESSES USING HYBRID TECHNIQUE EXPLORING MATHEMATICAL-PHYSICAL MODELS AND ARTIFICIAL NEURAL NETWORKS

Popis výsledku v původním jazyce

The optimization of the technological processes control is usually connected with mathematical models usage. Most of technical instruments for control on the level of own technology is not customized for the hard mathematical operations solving and in addition the computation with quality precisely models of the dynamic systems is very time consuming and together with the real time optimization is not really solvable. On the other hand the mathematical description of artificial neural networks (ANN) isvery simple and the algorithms of the learned ANN are easily implemented into existing technological processes control means. For successful using of the models on the base of ANN, the ANN needs to be rationally learned on the data which occupy all eventual variants which could occur in the real process including malfunction and crash states. But such a data is not practically possible to get from real technological process. There is possibility of off-line ANN learning with using data g

Název v anglickém jazyce

SIMULATION OF TECHNOLOGICAL PROCESSES USING HYBRID TECHNIQUE EXPLORING MATHEMATICAL-PHYSICAL MODELS AND ARTIFICIAL NEURAL NETWORKS

Popis výsledku anglicky

The optimization of the technological processes control is usually connected with mathematical models usage. Most of technical instruments for control on the level of own technology is not customized for the hard mathematical operations solving and in addition the computation with quality precisely models of the dynamic systems is very time consuming and together with the real time optimization is not really solvable. On the other hand the mathematical description of artificial neural networks (ANN) isvery simple and the algorithms of the learned ANN are easily implemented into existing technological processes control means. For successful using of the models on the base of ANN, the ANN needs to be rationally learned on the data which occupy all eventual variants which could occur in the real process including malfunction and crash states. But such a data is not practically possible to get from real technological process. There is possibility of off-line ANN learning with using data g

Druh

D - Stať ve sborníku

CEP obor

JG - Hutnictví, kovové materiály

OECD FORD obor

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Projekt

<a href="/cs/project/GA105%2F09%2F1366" target="_blank" >GA105/09/1366: Využití virtuální reality v simulaci a řízení výrobních procesů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

20th Anniversary International Conference on Metallurgy and Materials: METAL 2011

ISBN

978-80-87294-24-6

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

324-329

Název nakladatele

Tanger

Místo vydání

Ostrava

Místo konání akce

Brno

Datum konání akce

18. 5. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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