Data-Driven Multiobjective Optimization for Burden Surface in Blast Furnace With Feedback Compensation

Li, Y, Zhang, S, Zhang, J et al. (3 more authors) (2020) Data-Driven Multiobjective Optimization for Burden Surface in Blast Furnace With Feedback Compensation. IEEE Transactions on Industrial Informatics, 16 (4). pp. 2233-2244. ISSN 1551-3203

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Copyright, Publisher and Additional Information: © 2019 IEEE. This is an author produced version of a paper published in IEEE Transactions on Industrial Informatics. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Blast furnace (BF); burden surface; feedback compensation; kernel extreme learning machine (KELM); multiobjective optimization problem
Dates:
  • Published: April 2020
  • Accepted: 13 February 2019
  • Published (online): 2 April 2019
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 10 Apr 2019 15:28
Last Modified: 31 Jan 2020 21:43
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Identification Number: https://doi.org/10.1109/TII.2019.2908989

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