Abnormality Monitoring in the Blast Furnace Ironmaking Process Based on Stacked Dynamic Target-Driven Denoising Autoencoders

Accurate monitoring of abnormalities is of great significance to the stable operation of the blast furnace ironmaking process. This article proposes a data-driven model to accurately monitor the abnormal conditions of blast furnaces. Generally, data-driven models primarily rely on feature extraction...

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