DocumentCode
2065283
Title
Data engineering for neural net analysis of glass furnace characteristics
Author
Garner, Brian J. ; Ridley, G.J. ; Lowe, Peter J.
Author_Institution
Dept. of Comput. & Math., Deakin Univ., Geelong, Vic., Australia
fYear
1993
fDate
24-26 Nov 1993
Firstpage
317
Lastpage
320
Abstract
The authors report on the nature of the glass tinting process and provide an overview of the data engineering process that has been implemented to provide data from the Pilkington AIRCO furnace in an appropriate form for ANN modeling. A brief discussion of the general regression neural network architecture and its use as an adaptive model is also presented
Keywords
computer aided analysis; data acquisition; electric furnaces; glass industry; neural nets; ANN modeling; Dandenong plant; Pilkington AIRCO furnace; adaptive model; data engineering process; general regression neural network architecture; glass furnace characteristics; glass tinting process; neural net analysis; sputtering process; Artificial neural networks; Cathodes; Coatings; Communication system control; Data engineering; Glass manufacturing; Neural networks; Sputtering; Valves; Voltage control;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Neural Networks and Expert Systems, 1993. Proceedings., First New Zealand International Two-Stream Conference on
Conference_Location
Dunedin
Print_ISBN
0-8186-4260-2
Type
conf
DOI
10.1109/ANNES.1993.323014
Filename
323014
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