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Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1
ART2-Based Approach to Judge the State of the Blast Furnace
Jinan, China
October 16-October 18
ISBN: 0-7695-2528-8
ASCII Text
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Tieqiang Sun, Yixin Yin, Shengli Wu, Xuyan Tu, "ART2-Based Approach to Judge the State of the Blast Furnace," Intelligent Systems Design and Applications, International Conference on, vol. 1, pp. 118-122, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006.
 
 
BibTex
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@article{ 10.1109/ISDA.2006.108,
author = {Tieqiang Sun and Yixin Yin and Shengli Wu and Xuyan Tu},
title = {ART2-Based Approach to Judge the State of the Blast Furnace},
journal ={Intelligent Systems Design and Applications, International Conference on},
volume = {1},
year = {2006},
isbn = {0-7695-2528-8},
pages = {118-122},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.108},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Intelligent Systems Design and Applications, International Conference on
TI - ART2-Based Approach to Judge the State of the Blast Furnace
SN - 0-7695-2528-8
SP118
EP122
A1 - Tieqiang Sun,
A1 - Yixin Yin,
A1 - Shengli Wu,
A1 - Xuyan Tu,
PY - 2006
KW - null
VL - 1
JA - Intelligent Systems Design and Applications, International Conference on
ER -
 
Tieqiang Sun, University of Science & Technology Beijing; HeBei Polytechnic University, China
Yixin Yin, University of Science & Technology Beijing, China
Shengli Wu, University of Science & Technology Beijing, China
Xuyan Tu, University of Science & Technology Beijing, China
The complicate chemical reactions inside the blast furnace and many parameters affecting its working procedure during the process, it is very hard to judge the state of the blast furnace by traditional techniques, ART (Adaptive Resonance Theory) network accommodate these requirements through interactions between different subsystems, automatically detect clustering and form classes of the data structure. This paper proposes the factors of affecting the state of blast furnace; the model of ART2 for judging the state of the blast furnace is established; the state of the blast furnace is classified four sub-states: good, better, notice, bad. When a batch of new data is collected, the state of the blast furnace can be predicated by the ART2 neural network and achieves high veracity.
Citation:
Tieqiang Sun, Yixin Yin, Shengli Wu, Xuyan Tu, "ART2-Based Approach to Judge the State of the Blast Furnace," isda, vol. 1, pp.118-122, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006
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