A dynamic analytics method based on multistage modeling for a BOF steelmaking process

This paper proposes a dynamic analytics method based on the least squares support vector machine with a hybrid kernel to address real-time prediction problems in the converter steelmaking process. The hybrid kernel function is used to enhance the performance of the existing kernels. To improve the m...

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Bibliographic Details
Main Authors: Chang Liu, Lixin Tang, Jiyin Liu, Zhenhao Tang
Format: Default Article
Published: 2018
Subjects:
Other commerce, management, tourism and services not elsewhere classified
Mechanical engineering not elsewhere classified
Basic oxygen furnace (BOF)
Dynamic analytics
Hybrid kernel function
Least squares support vector machine (LSSVM)
Multistage modeling
Mechanical Engineering
Business and Management not elsewhere classified
Online Access:https://hdl.handle.net/2134/36031
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https://hdl.handle.net/2134/36031

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