Predicting the alloying element yield in a ladle furnace using principal component analysis and deep neural network-Reference-Cited by-同舟云学术

Predicting the alloying element yield in a ladle furnace using principal component analysis and deep neural network

Published:2022-12-21 Issue:2 Volume:30 Page:335-344
ISSN:1674-4799
Container-title:International Journal of Minerals, Metallurgy and Materials
language:en
Short-container-title:Int J Miner Metall Mater

Author:

Xin Zicheng,Zhang Jiangshan,Jin Yu,Zheng Jin,Liu Qing

Publisher

Springer Science and Business Media LLC

Subject

Materials Chemistry,Metals and Alloys,Geochemistry and Petrology,Mechanical Engineering,Mechanics of Materials

Link

https://link.springer.com/content/pdf/10.1007/s12613-021-2409-9.pdf

Reference38 articles.

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3. P. Yu, D. P. Zhan, Z. H. Jiang, D. L. Li, X. D. Yin, and Z. G. Ma, Development of a terminal composition prediction model for steel refining with ladle furnace, J. Mater. Metall., 5(2006), No. 1, p. 20.

4. G.B. Li, C.L. Zhao, S.H. Zhao, L.J. Wang, and W.W. Zhang, Development of LF refining composition prediction model, Angang Technol., 2009(4), p. 26.

5. N.K. Nath, K. Mandal, A.K. Singh, B. Basu, C. Bhanu, S. Kumar, and A. Ghosh, Ladle furnace on-line reckoner for prediction and control of steel temperature and composition, Ironmaking Steelmaking, 33(2006), No. 2, p. 140.

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