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Predictive Modelling of Nitrogen Content in Molten Metal During BOF Steelmaking Processes via Python-Based Machine Learning: A Benchmarking of Statistical Techniques

This study benchmarks eight Python-based machine learning models for predicting nitrogen content across four sequential stages of BOF steelmaking. A dataset of 291 metallic samples from 76 heats was employed, covering pig iron desulfurization (PHASE #1), crude steel before BOF tapping (PHASE #2), an...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Jaroslav Demeter, Branislav Buľko, Martina Hrubovčáková
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2026-04-01
Schriftenreihe:Applied Sciences
Schlagworte:
machine learning
nitrogen content prediction
BOF steelmaking
modelling
process optimization
digitalization
Online-Zugang:https://www.mdpi.com/2076-3417/16/8/3774
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