Generalised concept of artificial neural network models for demand forecasting of metallurgical commodities

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F11%3A86081934" target="_blank" >RIV/61989100:27360/11:86081934 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Generalised concept of artificial neural network models for demand forecasting of metallurgical commodities

Original language description

The article presents a generalised concept of artificial neural network forecasting models that would provide sufficient accuracy forecasts even in the period of significant fluctuation of demand for metallurgical commodities. The concept was deduced from two artificial neural network forecasting models which were applied in two processes of metallurgical companies and for two forecasting horizons. The first one was iron ore supply process where the objective was a short-term forecast of iron ore demand. The second was heavy plate cut shapes production process where a middle-term forecast was required.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

AE - Management, administration and clerical work

OECD FORD branch

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Project

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Continuities

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Publication year

2011

Confidentiality

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

Name of the periodical

Hutnik: Wiadomości Hutnicze

ISSN

1230-3534

e-ISSN

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Volume of the periodical

78

Issue of the periodical within the volume

9

Country of publishing house

PL - POLAND

Number of pages

3

Pages from-to

745-747

UT code for WoS article

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EID of the result in the Scopus database

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