Online Thickness Prediction of Hot Rolling Strip Based on ARO-XGBoost-Reference-Cited by-同舟云学术

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Online Thickness Prediction of Hot Rolling Strip Based on ARO-XGBoost

Published:2024-05-25 Issue: Volume:56 Page:161-166
ISSN:
Container-title:2024 36th Chinese Control and Decision Conference (CCDC)
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Author:

Shuo Huang¹,Fei Zhang¹,Lijun Wang²,Yongjun Zhang¹,Xuezhong Huang³

Affiliation:

1. University of Science and Technology Beijing,National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing,Beijing,China,100083

2. University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,Beijing,China,100083

3. Technology Research Institute of Guangxi Beigang New Material Co. LTD.,Guangxi,China,536017

Funder

National Key Research and Development Program of China

Guangxi Key Research and Development Program

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10587298/10587321/10587706.pdf?arnumber=10587706

Reference18 articles.

1. China steel rolling technology progress in the 13th five-year plan and prospection;Kang;Iron & Steel,2021

2. Robust predictive-model-control strategy for automatic gauge control in hot strip finishing milling;Yang;Control Theory & Applications,2011

3. Practical active disturbance rejection solution for monitoring automatic gauge control system with large time-delay;Wang;Control Theory & Applications,2012

4. Predicting hot-strip finish rolling thickness using stochastic configuration networks

5. Strip thickness prediction method based on improved border collie optimizing LSTM

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