Prediction of raw material batches for the production of clinker by means of artificial neural networks-Analysis of behaviour

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F15%3A43874009" target="_blank" >RIV/70883521:28140/15:43874009 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.scs-europe.net/dlib/2015/2015-0570.htm" target="_blank" >http://www.scs-europe.net/dlib/2015/2015-0570.htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7148/2015-0570" target="_blank" >10.7148/2015-0570</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction of raw material batches for the production of clinker by means of artificial neural networks-Analysis of behaviour

Popis výsledku v původním jazyce

This research deals with the analysis of the behaviour of artificial neural nets for prediction of raw material batches for the production of clinker. During the production several oxides that are present in raw materials in quarries has to be extractedfor homogenization of the mixture suitable for clinker production. There is some delay between the measurement of the mixture and the material which is send from quarry. It is necessary to "send" precise chemical composition to ensure a good quality of clinker and resulting product - cement. ANN are suitable for such kind of time-independent prediction. The results show that not all oxides are necessary to use for the prediction of one oxide. The ANN were designed into several nets with one input similarly as pseudo neural networks are able to work. The results will be used for the purpose of further research of pseudo neural nets which currently serve only as classifiers.

Název v anglickém jazyce

Prediction of raw material batches for the production of clinker by means of artificial neural networks-Analysis of behaviour

Popis výsledku anglicky

This research deals with the analysis of the behaviour of artificial neural nets for prediction of raw material batches for the production of clinker. During the production several oxides that are present in raw materials in quarries has to be extractedfor homogenization of the mixture suitable for clinker production. There is some delay between the measurement of the mixture and the material which is send from quarry. It is necessary to "send" precise chemical composition to ensure a good quality of clinker and resulting product - cement. ANN are suitable for such kind of time-independent prediction. The results show that not all oxides are necessary to use for the prediction of one oxide. The ANN were designed into several nets with one input similarly as pseudo neural networks are able to work. The results will be used for the purpose of further research of pseudo neural nets which currently serve only as classifiers.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings - 29th European Conference on Modelling and Simulation, ECMS 2015

ISBN

978-0-9932440-0-1

ISSN

—

e-ISSN

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Počet stran výsledku

6

Strana od-do

570-575

Název nakladatele

ECMS - European Council for Modelling and Simulation

Místo vydání

Albena (Varna)

Místo konání akce

Albena (Varna)

Datum konání akce

26. 5. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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