DocumentCode :
530645
Title :
The prediction of AOD furnace´s end point carbon content based on wavelet neural network
Author :
Li, Hui ; Duan, Ran ; Zhang, Dejiang
Author_Institution :
Coll. of Electr. & Electron. Eng., Changchun Univ. of Technol., Changchun, China
Volume :
4
fYear :
2010
fDate :
24-26 Aug. 2010
Firstpage :
371
Lastpage :
373
Abstract :
AOD furnace smelting low-carbon ferrochrome for the actual situation of the affected end AOD stove carbon content factor, the wavelet neural network prediction model of carbon content in the end, the actual production data using 200-stove model is trained,and the other furnace carbon content of 12 to predict the results, wavelet neural network based on end point carbon content prediction model has high accuracy, showing that its in metallurgy with the significant advantages and great potential.
Keywords :
carbon; furnaces; neural nets; production engineering computing; smelting; wavelet transforms; AOD furnace end point carbon content prediction; AOD stove carbon content factor; furnace smelting; low-carbon ferrochrome; wavelet neural network; Barium; Carbon; AOD furnace; prediction of end point; wavelet neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
Type :
conf
DOI :
10.1109/CMCE.2010.5610140
Filename :
5610140
Link To Document :
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