DocumentCode
2283325
Title
Breakout Prediction Based on BP Neural Network of LM Algorithm in Continuous Casting Process
Author
Ben-guo Zhang ; Qiang Li ; Ge Wang ; Ying Gao
Author_Institution
Coll. of Mech. Eng., Yanshan Univ., Qinhuangdao, China
Volume
1
fYear
2010
fDate
13-14 March 2010
Firstpage
765
Lastpage
768
Abstract
An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that verified the feasibility of the model.
Keywords
backpropagation; casting; neural nets; steel industry; BP neural network; LM algorithm; Levenberg-Marquardt algorithm; breakout prediction; continuous casting process; learning algorithm; molten steel; Accidents; Casting; Educational institutions; Materials science and technology; Neural networks; Predictive models; Strips; Temperature measurement; Thickness measurement; Time measurement; BP neural network; LM algorithm; breakout prediction; continuous casting;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location
Changsha City
Print_ISBN
978-1-4244-5001-5
Electronic_ISBN
978-1-4244-5739-7
Type
conf
DOI
10.1109/ICMTMA.2010.403
Filename
5458911
Link To Document