DocumentCode
2525251
Title
Development of Integration Prediction Model for Alumina Raw Slurry Quality
Author
Zhifeng, Qiu ; Weihua, Gui ; Chunhua, Yang ; Yalin, Wang
Author_Institution
Sch. of Inf. Sci. & Eng., Central South Univ. of Technol., Changsha
Volume
3
fYear
2006
fDate
Aug. 30 2006-Sept. 1 2006
Firstpage
128
Lastpage
131
Abstract
The blending process plays an important role in alumina production. Forecasting the alumina raw slurry quality accurately has great significance for improving alumina quality. This paper combines first principles, in the form of mass balance equations, with artificial neural networks (ANNs) as estimators for some of the important process parameters as well as compensator for mass balance equation in alumina raw meal quality modeling. The performance verified its feasibility and operability
Keywords
aluminium industry; blending; neural nets; production engineering computing; alumina production; alumina raw slurry quality; artificial neural network; blending process; integration prediction model; mass balance equation; Artificial neural networks; Calcium; Equations; Information science; Iron; Neural networks; Predictive models; Production; Raw materials; Slurries;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location
Beijing
Print_ISBN
0-7695-2616-0
Type
conf
DOI
10.1109/ICICIC.2006.437
Filename
1692133
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