Quantitative Model Study on Desulfurizer Quality of KR Desulfurization

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Abstract:

In this paper, according to the KR desulphurization historical data, samples are refined and optimized through prior knowledge, to better meet the requirements of establishing desulfurizer quality quantitative model; then samples are classified using DBSCAN clustering algorithm, on the basis of which desulfurizer quality quantitative model is established.

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Periodical:

Advanced Materials Research (Volumes 926-930)

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392-395

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May 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] P.I. Yugov, A. Romberg, and D. Yang: Metallurgist, Vol. 44 (2000) No. 11, p.556.

Google Scholar

[2] F.Y. Li, C.H. Yu, Z.H. Zhou, etc.,: Steelmaking, Vol. 16 (2000) No. 1, p.13.

Google Scholar

[3] B. Deo, R.K. Lingamaneni, A. Dey, and R. Boom: Materials and Manufacturing Processes, Vol. 20 (2005) No. 3, p.407.

Google Scholar

[4] Z.J. Rong, B.B. Dan and J. G, Yi: Advanced Data Mining and Applications, Vol. 3584(2005), p.728.

Google Scholar

[5] H.S. Zhang, D.P. Zhan and Z.H. Jiang: Iron & Steel, Vol. 42 (2007) No. 3, p.30.

Google Scholar

[6] M. Ester, H. P. Kriegel, J. Sander and X. Xu: Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining (Portland, Oregon, August 2–4, 1996). Vol. 96, p.226.

Google Scholar