Development of integration prediction model for alumina raw slurry quality

摘要

The blending process plays an important role in Alumina production. Forecasting the alumina raw slurry quality accurately has great significance for improving alumina quality. This paper combines first principles, in the form of mass balance equations, with artificial neural networks(ANNs) as estimators for some of the important process parameters as well as compensator for mass balance equation in alumina raw meal quality modeling. The performance verified its feasibility and operability.