Prediction Model of End-Point Phosphorus Content in EAF Steelmaking Based on BP Neural Network with Periodical Data Optimization

Prediction Model of End-Point Phosphorus Content in EAF Steelmaking Based on BP Neural Network with Periodical Data Optimization

The phosphorus (P) content of molten steel is of great importance for the quality of steel products in the electric arc furnace (EAF) steelmaking process. At present, the initial conditions of smelting process in the prediction of end-point P content are still the core part. However, few studies foc...

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Bibliographic Details
Main Authors: Yuchi Zou, Lingzhi Yang, Bo Li, Zefan Yan, Zhihui Li, Shuai Wang, Yufeng Guo
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Metals
Subjects:
electric arc furnace steelmaking
end-point phosphorus content
modeling prediction
artificial neural network
Online Access:https://www.mdpi.com/2075-4701/12/9/1519

Internet

https://www.mdpi.com/2075-4701/12/9/1519

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