Application of neural-network for improving accuracy of roll-force model in hot-rolling mill

Control Engineering Practice

Volumn 10, Issue 4, 2002, Pages 473-478

  Lee, Dukman ^a   Lee, Yongsug ^a  

^a POSCO   (South Korea)

Author keywords

Long term learning; Neural network; Rolling force; Short term learning

Indexed keywords

ELECTRIC COILS; ROLLING MILLS; STATISTICAL METHODS;

THICKNESS ACCURACY;

NEURAL NETWORKS;

FORCE; HOT ROLLING; MILL; NEURAL NETWORK; STATISTICAL ANALYSIS;

EID: 0036531941     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0967-0661(01)00143-5     Document Type: Article

References (8)

1. Reliable roll force prediction in cold mill using multiple neural networks
2. Training feedforward networks with the marquardt algorithm
3. Application of ann in combination with mathematical model in prediction of rolling load of the finishing stands in hsm
4. Artificial neural networks for the presetting of a steel temper mill
5. Application of linear regression analysis in accuracy assessment of rolling-force calculations
6. Application of neural networks in rolling mill automation
7. Technologies of flying gauge change in fully continuous cold rolling mill for thin gauge steel strips