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A hybrid neural-network/mathematical prediction model for tandem cold mill

  • Published:1997-12 Issue:3-4 Volume:33 Page:453-456
  • ISSN:0360-8352
  • Container-title:Computers & Industrial Engineering
  • language:en
  • Short-container-title:Computers & Industrial Engineering

Author:

Cho Sungzoon,Jang Min,Yoon Sungcheol,Chot Yongjoong,Cho Hyungsuk

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference6 articles.

1. Learning internal representation by error propagation;Rumelhart,1986

2. Improvement of set-up model for tandem cold rolling mill;Lee,1994

3. Guide Book for Mathematical Model of 1st Cold Mill;Hitachi Co Ltd,1980

4. Artificial neural networks for the presetting of a steel temper mill;Pican;IEEE Expert,1996

5. Application of neural networks in rolling mill automation;Portmann;Iron and Steel Engineer,1995

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1. Physics-based and data-driven hybrid modeling in manufacturing: a review;Production & Manufacturing Research;2024-01-18

2. Multiobjective Optimization of Roll-Forming Procedure Using NSGA-II and Type-2 Fuzzy Neural Network;IEEE Transactions on Automation Science and Engineering;2023

3. Methodology of developing mathematical-ANN hybrid model based mill setup model for hot strip rolling;International Journal for Computational Methods in Engineering Science and Mechanics;2021-02-17

4. Prediction of Mechanical Properties of Fe 415 Steel in Hot Rolling Process Using Artificial Neural Network;Transactions of the Indian Institute of Metals;2020-03-12

5. MATHEMATICAL-ARTIFICIAL NEURAL NETWORK HYBRID MODEL TO PREDICT ROLL FORCE DURING HOT ROLLING OF STEEL;International Journal of Computational Materials Science and Engineering;2013-03
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