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J. Kusiak, L. Sztangret, M. Pietrzyk, "Effective Strategies of the Optimization of Industrial Metallurgical Processes", in Y. Tsompanakis, (Editor), "Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 34, 2013. doi:10.4203/ccp.103.34

Keywords: metamodelling, artificial neural network, Kriging, process modelling, optimization.

Summary

The main objective of the paper is presentation of the strategy of reduction of the computation time necessary for the optimization procedure. The use of metamodels of the analyzed processes is presented. The metamodel replaces the model of analyzed process and allows a significant reduction of the computation time and thus the optimization of analyzed process is easier. The paper discusses the idea of metamodelling and compares the results of two techniques: the Kriging method and artificial neural network (ANN) applied to the benchmark functions and to the real industrial problem of laminar cooling of steel strips.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 103 PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING Edited by: Y. Tsompanakis Paper 34 Effective Strategies of the Optimization of Industrial Metallurgical Processes J. Kusiak, L. Sztangret and M. Pietrzyk AGH University of Science and Technology, Krakow, Poland doi:10.4203/ccp.103.34 purchase the full-text of this paper Full Bibliographic Reference for this paper J. Kusiak, L. Sztangret, M. Pietrzyk, "Effective Strategies of the Optimization of Industrial Metallurgical Processes", in Y. Tsompanakis, (Editor), "Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 34, 2013. doi:10.4203/ccp.103.34 Keywords: metamodelling, artificial neural network, Kriging, process modelling, optimization. Summary The main objective of the paper is presentation of the strategy of reduction of the computation time necessary for the optimization procedure. The use of metamodels of the analyzed processes is presented. The metamodel replaces the model of analyzed process and allows a significant reduction of the computation time and thus the optimization of analyzed process is easier. The paper discusses the idea of metamodelling and compares the results of two techniques: the Kriging method and artificial neural network (ANN) applied to the benchmark functions and to the real industrial problem of laminar cooling of steel strips. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £42 +P&P)
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