Selecting representative prototypes for prediction the oxygen activity in electric arc furnace

Authors:
Marcin Blachnik;Mirosław Kordos;Tadeusz Wieczorek;Sławomir Golak
Affiliations:
Department of Management and Informatics, Silesian University of Technology, Katowice, Poland;Department of Mathematics and Informatics, University of Bielsko-Biala, Bielsko-Biała, Poland;Department of Management and Informatics, Silesian University of Technology, Katowice, Poland;Department of Management and Informatics, Silesian University of Technology, Katowice, Poland
Venue:
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Year:
2012

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Abstract

Selecting a set of representative prototypes in prediction systems enable us to generate prototype based rules (P-Rules), which constitute a very powerful means of providing domain experts with knowledge about the data and the process depicted by the data. P-rules has already proved very useful in classification tasks. This paper investigates application of P-rules to regression problems. The problem of our concern is prediction of oxygen activity in an electric arc furnace during steel scrap melting. For that purpose we use a new algorithm for determining prototype positions, which is based on conditional clustering. Also a comparison between the new algorithm and the classical clustering-based methods for prototype extraction is described.