Combination Model Based on CBR and SVM for BOF Oxygen Volume Calculation

Abstract:

Oxygen blowing volume control is very important in Basic Oxygen Furnace (BOF) steelmaking. A combination model based on information theory and artificial intelligence technology is proposed for oxygen blowing volume calculation. The combination model is composed of Case-based Reasoning (CBR) model and Support Vector Machine (SVM) model. In CBR model, the mutual information is introduced in case retrieval step to determine the weights of attributes. In SVM model, the mutual information is adopt to distinguish the importance of input variables by setting a different weight to each variable. The CBR model is viewed as experience based model and the SVM model is viewed as data based model. To model the oxygen blowing volume accurately, CBR model and SVM model are combined. Tests on a 180 ton BOF data are implemented to validate the effectiveness of the proposed method.

• Periodical: Advanced Materials Research (Volumes 634-638)
• Pages: 3741-3747
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.634-638.3741
• Online since: January 2013
• Authors: Jun Xing, Jian Jun Peng, Yan Hui Yin
• Keywords: Basic Oxygen Furnace, Case-Based Reasoning (CBR), Mutual Information (MI), Support Vector Machine (SVM)

References

[1] Valyon J, Horvath G. A sparse robust model for a Linz–Donawitz steel converter[J]. IEEE Transactions on Instrumentation and Measurement, 2009, 58(8): 2611-2617.

DOI: 10.1109/tim.2009.2015638

[2] Zhu G J, Liang B C. Optimum model of static control on BOF steelmaking process[J]. Steelmaking, 1999, 15(4): 25-28. (In Chinese).

[3] Cox I J, Levis R W, Ransing R S. Application of neural computing in basic oxygen steelmaking[J]. Journal of Material Processing Technology, 2002, 120(1-3): 310-315.

DOI: 10.1016/s0924-0136(01)01136-0

[4] Ullman S, Basri R. Recognition by linear combinations of models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(10): 992-1006.

DOI: 10.1109/34.99234

[5] Neto L.C., 1981. End-blow model for control of LD converters and statistic analysis of its performance. Master's Thesis, Federal University of Minas Gerais, Brazil.

[6] Birk W, Johansson A, Medvedev A, Johansson R. Model-based Estimation of Molten Metal Analysis in the LD Converter: Experiments at SSAB Tunnplåt AB in Luleå. IEEE Transactions on Industry Applications, 2002, 38(2): 565-570.

DOI: 10.1109/28.993180

[7] Kubat, C., H. Taskin, et al. Bofy-fuzzy logic control for the basic oxygen furnace (BOF). Robotics and Autonomous Systems. 2004, 49: 193-205.

DOI: 10.1016/j.robot.2004.09.007

[8] N. Reyhani, J. Hao, Y. Ji, and A. Lendasse. Mutual information and gamma test for input selection. European Symposium on Artificial Neural Networks, Bruges, Belgium, (2005).

[9] Yuan-Hsin Tung, Shian-Shyong Tseng, Jui-Feng Weng, Tsung-Ping Lee, Anthony Y.H. Liao b, Wen-Nung Tsai. A rule-based CBR approach for expert finding and problem diagnosis. Expert System with Applications. 2010, 37: 2427–2438.

DOI: 10.1016/j.eswa.2009.07.037

[10] Aasia Khanum, Muid Mufti, M. Younus Javed, M. Zubair Shafiq. Fuzzy case-based reasoning for facial expression recognition. Fuzzy Sets and Systems. 2009, 160 (2): 231-250.

DOI: 10.1016/j.fss.2008.05.022

[11] Hyunchul Ahn, Kyoung-jae Kim. Global optimization of case-based reasoning for breast cytology diagnosis. Expert Systems with Applications. 2009, 36(1): 724-734.

DOI: 10.1016/j.eswa.2007.10.023

[12] Guillermo Cortes Robles, Stéphane Negny, Jean Marc Le Lann. Case-based reasoning and TRIZ: A coupling for innovative conception in Chemical Engineering. Chemical Engineering and Processing. 2009, 48(1): 239-249.

DOI: 10.1016/j.cep.2008.03.016

[13] Chang P C, Liu C H, Lai R K. A fuzzy case-based reasoning model for sales forecasting in print circuit board industries[J]. Expert Systems with Applications, 2008, 34(3): 2049-(2058).

DOI: 10.1016/j.eswa.2007.02.011

[14] Huang M J, Chen M Y, Lee S C. Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis[J]. Expert Systems with Applications, 2007, 32: 856-867.

DOI: 10.1016/j.eswa.2006.01.038

[15] Virkki T, Reners G L L. A case-based reasoning safety decision-support tool: nextcase/safety[J]. Expert Systems with Applications, 2009, 36(7): 10374-10380.

DOI: 10.1016/j.eswa.2009.01.059

[16] V. Vapnik. The nature of statistical learning theory. Springer-Verlag, (1995).