Neural predictor of the end point in a converter
DOI:
https://doi.org/10.3989/revmetalm.2004.v40.i6.299Keywords:
LD Converter, model, Neural Network.Abstract
The paper presents a system based on neural networks which is capable of predicting the so-called End Point of a converter by exploiting the measurements of the oxygen content and of the temperature in order to predict the final carbon content. Due to several disadvantages of current LD algebraic model and the usage of modem process in steel plant, a new model based on neural network and knowledge base is designed. The new model allowed to obtain excellent simulation result and satisfied online testing report.
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Published
2004-12-30
How to Cite
Valentini, R., Colla, V., & Vannucci, M. (2004). Neural predictor of the end point in a converter. Revista De Metalurgia, 40(6), 416–419. https://doi.org/10.3989/revmetalm.2004.v40.i6.299
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