DocumentCode
1931495
Title
The application of genetic algorithm and BP neural network for control of hot-rolled steel pipe system
Author
Xu, Qingzeng ; Yang, Meiyan ; Zhang, Hanliang
Author_Institution
Comput. Sci. & Inf. Eng. Coll., Tianjin Univ. of Sci. & Technol., Tianjin, China
Volume
3
fYear
2010
fDate
9-11 July 2010
Firstpage
221
Lastpage
223
Abstract
Using genetic algorithm and BP neural network method of combining, this paper has established dynamic forward feedback correction model and has completed the automatic adjustment of the various parameters required for rolling steel pipe, and has made rolled steel pipe system work at the best value. After the actual data validation, the model can more accurately pre-adjusted parameters to achieve intelligent control.
Keywords
backpropagation; feedback; genetic algorithms; hot rolling; neurocontrollers; pipes; steel; BP neural network; dynamic forward feedback correction model; genetic algorithm; hot rolling; intelligent control; steel pipe system; Computational modeling; Fitting; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5563724
Filename
5563724
Link To Document