A Stacked Autoencoder With Sparse Bayesian Regression for End-Point Prediction Problems in Steelmaking Process

The steelmaking process in the iron and steel industry involves complicated physicochemical reactions. The main aim of steelmaking is to adjust the quality of molten steel. During the steel-tapping process, the temperature and carbon content are the most essential quality indices for end-point prediction. This article presents a novel machine learning framework for the endpoint prediction problems...