DocumentCode
3207590
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
fYear
2002
fDate
2002
Firstpage
2
Lastpage
6
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
Print_ISBN
0-7695-1709-9
Type
conf
DOI
10.1109/SBRN.2002.1181426
Filename
1181426
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