Conference Paper

A BP Neural Network Predictor Model for Desulfurizing Molten Iron.

DOI: 10.1007/11527503_86 In proceeding of: Advanced Data Mining and Applications, First International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Proceedings
Source: DBLP

ABSTRACT Desulfurization of molten iron is one of the stages of steel production process. A back-propagation (BP) artificial neural
network (ANN) model is developed to predict the operation parameters for desulfurization process in this paper. The primary
objective of the BP neural network predictor model is to assign the operation parameters on the basis of intelligent algorithm
instead of the experience of operators. This paper presents a mathematical model and development methodology for predicting
the three main operation parameters and optimizing the consumption of desulfurizer. Furthermore, a software package is developed
based on this BP ANN predictor model. Finally, the feasibility of using neural networks to model the complex relationship
between the parameters is been investigated.

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