Use of the control-steering systems in blast furnace technology contributes to the improvement of the quality of hot metal, which can be expressed by desirable and stable chemical composition and required temperature of hot metal at the tap. The paper presents the possibility of using artificial neural network as part of BF technology supporting system, and in particular its use to predict silicon, sulfur and phosphorus containing in hot metal. The models of neural networks have been created on the industrial operation basis of blast furnace No. 5 Arcelor Mittal Poland Krakow.Keywords: Blast furnace, neural networks, prediction of hot metal composition
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