Intelligent predictive model of ventilating capacity of imperial smelt furnace

Abstract

In order to know the ventilating capacity of imperial smelt furnace (ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks (ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.

Keywords

imperial smelt furnace / ventilating capacity / intelligent predictive model / artificial neural network / gray theory / adaptive fuzzy combination

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