Application of Adaptable Neural Networks for Rolling Force Set-Up in Optimization of Rolling Schedules
This paper presents two optimization procedures–single and multi objective optimization for 1370mm tandem cold rolling schedules, in which back propagation (BP) neural network is adopted to predict the rolling force instead of traditional models. Analysis and comparison with existing schedules are offered. The results show that the proposed schedules are more promising.
KeywordsBack Propagation Back Propagation Neural Network Roll Speed Rolling Force Adaptable Neural Network
Unable to display preview. Download preview PDF.
- 3.Zhao, H.J., Zhang, Y.H., Hu, H.T.: The Optimized Design of Copper Strips Rolling Rules by Dynamic Programming Method. Journal of Southern Institute of Metallurgy 22(4), 243–246 (2001)Google Scholar
- 4.Di, H.S., Xu, J.Z., Gong, D.Y.: Effect of Load Distribution on Strip Crown in Hot Strip Rolling. J. Maser. Sci. Technol. 20(3), 330–334 (2004)Google Scholar