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
         
        
        
            fDate : 
May 31 2014-June 2 2014
         
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Control and Decision Conference (2014 CCDC), The 26th Chinese
         
        
            Conference_Location : 
Changsha
         
        
            Print_ISBN : 
978-1-4799-3707-3
         
        
        
            DOI : 
10.1109/CCDC.2014.6852882