"RIV/61989100:27360/11:86081934!RIV12-MSM-27360___" . "Feliks, J." . "2"^^ . "[34A83E44A78D]" . . "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." . "27360" . . . "PL - Polsk\u00E1 republika" . "heavy plate cut shapes; iron ore; metallurgical commodities; demand forecasting; artificial neural network"@en . . . . . "RIV/61989100:27360/11:86081934" . . . "9" . "1230-3534" . "78" . "Lenort, Radim" . "200906" . . . "Hutnik: Wiadomo\u015Bci Hutnicze" . . "3"^^ . . "Generalised concept of artificial neural network models for demand forecasting of metallurgical commodities"@en . . . "N" . . "Generalised concept of artificial neural network models for demand forecasting of metallurgical commodities"@en . "Generalised concept of artificial neural network models for demand forecasting of metallurgical commodities" . "1"^^ . "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."@en . . "Generalised concept of artificial neural network models for demand forecasting of metallurgical commodities" .