Predictive Modeling and Control Analysis of Fuel Ratio in Blast Furnace Ironmaking Process Based on Machine Learning-Reference-Cited by-同舟云学术

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Predictive Modeling and Control Analysis of Fuel Ratio in Blast Furnace Ironmaking Process Based on Machine Learning

Published:2023-07-18 Issue:9 Volume:75 Page:3975-3984
ISSN:1047-4838
Container-title:JOM
language:en
Short-container-title:JOM

Author:

Jiang Dewen,Wang Zhenyang^ORCID,Li Kejiang,Zhang Jianliang,Zhang Song

Funder

the National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

General Engineering,General Materials Science

Link

https://link.springer.com/content/pdf/10.1007/s11837-023-06010-2.pdf

Reference49 articles.

1. R. Cavicchioli, W.J. Ripple, K.N. Timmis, F. Azam, L.R. Bakken, M. Baylis, M.J. Behrenfeld, A. Boetius, P.W. Boyd, and A.T. Classen, Nat. Rev. Microbiol. 17, 569 (2019).

2. H. Suopajärvi, K. Umeki, E. Mousa, A. Hedayati, H. Romar, A. Kemppainen, C. Wang, A. Phounglamcheik, S. Tuomikoski, N. Norberg, A. Andefors, M. Öhman, U. Lassi, and T. Fabritius, Appl. Energy 213, 384 https://doi.org/10.1016/j.apenergy.2018.01.060 (2018).

3. A. Schoedel, Z. Ji, and O.M. Yaghi, Nat. Energy 1, 1 (2016).

4. D. Zhou, K. Xu, J. Bai, and D. He, Fuel 316, 123349 (2022).

5. Z. Guo, J. Zhang, K. Jiao, T. Gao, Y. Zong, and J. Zhang, Ironmak. Steelmak. 48, 685 (2021).

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1. Ironmaking process under artificial intelligence technology: A review;Ironmaking & Steelmaking: Processes, Products and Applications;2024-09-02

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