Answers are grounded in this paper and cite their sources.
The present work presents a model based on fuzzy logic tools to predict and simulate the hot metal temperature in a blast furnace (BF). As input variables this model uses the control variables of a current BF such as moisture, pulverised coal injection, oxygen addition, mineral/coke ratio and blast volume, and it yields as a result of the hot metal temperature. The variables employed to develop the model have been obtained from data supplied by current sensors of a Spanish BF. In the model training stage the adaptive neurofuzzy inference system and the subtractive clustering algorithms have been used.
No takes yet. Share an insight, caveat, or question.
Martín et al. (2007) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: