DocumentCode
176800
Title
BTP prediction of sintering process by using multiple models
Author
Jialin Wang ; Xiaoli Li ; Yang Li ; Kang Wang
Author_Institution
Sch. of Autom. & Electr. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
fYear
2014
fDate
May 31 2014-June 2 2014
Firstpage
4008
Lastpage
4012
Abstract
Burning Through Point (BTP) state is a very important parameter for sintering process. A lot of researches for the modeling of BTP have been made, but the precise model is not very easy to find, so the prediction based on modeling cannot be carried out effectively. This paper presents fuzzy neural network structure and multiple model algorithms which can process incomplete, ambiguous information and gives an effective model for sintering process. The simulation result is made to show the effectiveness of the proposed algorithm.
Keywords
combustion; fuzzy neural nets; production engineering computing; sintering; BTP prediction; burning through point state; fuzzy neural network structure; incomplete ambiguous information processing; multiple model algorithms; sintering process; Decision support systems; BTP; Fuzzy Neural Network; Multiple Model Algorithm; Sintering Process;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location
Changsha
Print_ISBN
978-1-4799-3707-3
Type
conf
DOI
10.1109/CCDC.2014.6852882
Filename
6852882
Link To Document