Evaluation, Prediction, and Feedback of Blast Furnace Hearth Activity Based on Data‐Driven Analysis and Process Metallurgy

For complex, difficult‐to‐control, and hour‐delay blast furnace (BF) systems, the quantitative characterization, prediction, and adjustment of the BF hearth activity are significant in improving the furnace status. In this study, data including raw fuel, process operation, smelting state, and slag a...

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Vydané v:	Steel research international Ročník 95; číslo 2
Hlavní autori:	Shi, Quan, Tang, Jue, Chu, Mansheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Weinheim Wiley Subscription Services, Inc 01.02.2024
Predmet:	data-driven analyses Genetic algorithms hearth activities Machine learning Metallurgical analysis prediction and feedbacks process metallurgies Process metallurgy time lags
ISSN:	1611-3683, 1869-344X
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