Model of multilayer artificial neural network for prediction of iron ore demand

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F11%3A86081883" target="_blank" >RIV/61989100:27360/11:86081883 - 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

Model of multilayer artificial neural network for prediction of iron ore demand

Popis výsledku v původním jazyce

With regards to many effects which can disrupt the delivery schedule of iron ore to a company, this raw material must be ordered well in advance. Determination of the required order volume results from prediction of iron ore demand. With respect to the fluctuations on the metallurgical commodity market, it is very difficult to use classical prediction models based on time series analysis. A typical example when models based solely on historical time series can not be used to predict iron ore demand is the world economic crisis period, because the demand for metallurgical commodities witnesses a sharp decrease. The article presents prediction model based on multilayer artificial neural network which takes into account not only historical data of iron ore demand but also information regarding the current situation on the world steel market and the iron ore stock volume of a given metallurgical company. The model is designed in such a way that the output is represented by the demand predi

Název v anglickém jazyce

Model of multilayer artificial neural network for prediction of iron ore demand

Popis výsledku anglicky

With regards to many effects which can disrupt the delivery schedule of iron ore to a company, this raw material must be ordered well in advance. Determination of the required order volume results from prediction of iron ore demand. With respect to the fluctuations on the metallurgical commodity market, it is very difficult to use classical prediction models based on time series analysis. A typical example when models based solely on historical time series can not be used to predict iron ore demand is the world economic crisis period, because the demand for metallurgical commodities witnesses a sharp decrease. The article presents prediction model based on multilayer artificial neural network which takes into account not only historical data of iron ore demand but also information regarding the current situation on the world steel market and the iron ore stock volume of a given metallurgical company. The model is designed in such a way that the output is represented by the demand predi

Druh

D - Stať ve sborníku

CEP obor

AE - Řízení, správa a administrativa

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

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

5

Strana od-do

1206-1210

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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