@inproceedings{7f0240dc8f2a472a8ba097df897bce22,
title = "Artificial intelligence and data-driven modeling in ironmaking - Potential and limitations",
abstract = "The revival of artificial intelligence (AI) promises to offer solutions in particular for complex systems that are difficult to model with classical methods. An overview of AI solutions in ironmaking is provided and their strengths and weaknesses are discussed. Topics such as the applicability for typical problem groups, pre-conditions regarding required data quality and completeness of data sets, reliability, and combination with classical approaches are covered. Further, the deployment and integration of black box models into control systems and the related stability are discussed.",
keywords = "Artificial intelligence, Data analytics, Ironmaking, Process optimization",
author = "Dieter Bettinger and Harald Fritschek and Adnan Husakovic and Petra Krahwinkler and Martin Schaler and Sonja Strasser",
note = "Publisher Copyright: {\textcopyright} 2021 by the Association for Iron \& Steel Technology.; AISTech 2021 Iron and Steel Technology Conference ; Conference date: 29-06-2021 Through 01-07-2021",
year = "2021",
doi = "10.33313/382/196",
language = "English",
series = "AISTech - Iron and Steel Technology Conference Proceedings",
publisher = "Association for Iron and Steel Technology, AISTECH",
pages = "1919--1931",
booktitle = "AISTech 2021 - Proceedings of the Iron and Steel Technology Conference",
address = "United States",
}