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 :
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