Title : 
Application of feedforward neural networks for soft sensors in the sugar industry
         
        
            Author : 
Devogelaere, Dirk ; Rijckaert, Marcel ; Leon, Osvaldo Goza ; Lemus, Gil Cruz
         
        
            Author_Institution : 
Chem. Eng. Dept., Katholieke Univ., Leuven, Belgium
         
        
        
        
        
        
            Abstract : 
Neural networks have been successfully applied as intelligent sensors for process modeling and control. In this paper, the application of soft sensors in the cane sugar industry is discussed. A neural network is trained on historical data to predict process quality variables so that it can replace the lab-test procedure. An immediate benefit of building intelligent sensors is that the neural network can predict product quality in a timely manner.
         
        
            Keywords : 
feedforward neural nets; food processing industry; intelligent sensors; process control; quality control; feedforward neural networks; intelligent sensors; nonlinear black-box prediction; process control; quality control; soft sensors; sugar industry; Chemical engineering; Chemical sensors; Distributed control; Feedforward neural networks; Intelligent networks; Intelligent sensors; Investments; Neural networks; Process control; Sugar industry;
         
        
        
        
            Conference_Titel : 
Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
         
        
            Print_ISBN : 
0-7695-1709-9
         
        
        
            DOI : 
10.1109/SBRN.2002.1181426