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Using of self-teaching systems for steel brand identification in oxygen converter prodution

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Category: Information technologies, systems analysis and administration

Last Updated on 27 November 2012

Published on 26 November 2012

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Authors:

T.A. Zheldak, Candidate of Technical Sciences, Senior Lecturer of the System Analysis And Control Department of the State Higher Educational Institution “National Mining University”, Dnipropetrovsk, Ukraine

N.A. Kucherenko, Student of State Higher Educational Institution “National Mining University”, Dnipropetrovsk, Ukraine

The analysis of the technological process of low-carbon steel in basic oxygen furnace and the information known before purging starts. To classify the grade of steel it was selected the self-learning system in the form of a two-layer neural network based on perceptrons. Experimental studies on training and use of the network have been carried out. Conclusions about the network and its learning algorithm have been drawn. Suggestions of probable improvement of the system have been formulated.

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2011_01 Zheld
2012-11-27  340.63 KB  1164

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