Predicting the rolling force in hot steel rolling mill using an ensemble model Frayman, Yakov, Rolfe, Bernard, Hodgson, Peter and Webb, G.I 2002, Predicting the rolling force in hot steel rolling mill using an ensemble model, in Artificial intelligence and applications: proceedings of the second IASTED International Conference, ACTA Press, New York, N.Y., pp. 143-148. Attached Files Name Description MIMEType Size Downloads Title Predicting the rolling force in hot steel rolling mill using an ensemble model Author(s) Frayman, Yakov Rolfe, Bernard orcid.org/0000-0001-8516-6170 Hodgson, Peter Webb, G.I Conference name IASTED International Conference (2nd : 2002 : Malaga, Spain) Conference location Malaga, Spain Conference dates 9-12 September 2002 Title of proceedings Artificial intelligence and applications: proceedings of the second IASTED International Conference Editor(s) Hamza, M.H. Publication date 2002 Start page 143 End page 148 Publisher ACTA Press Place of publication New York, N.Y. Keyword(s) Engineering Applications Summary Accurate prediction of the roll separating force is critical to assuring the quality of the final product in steel manufacturing. This paper presents an ensemble model that addresses these concerns. A stacked generalisation approach to ensemble modeling is used with two sets of the ensemble model members, the first set being learnt from the current input-output data of the hot rolling finishing mill, while another uses the available information on the previous coil in addition to the current information. Both sets of ensemble members include linear regression, multilayer perceptron, and k-nearest neighbor algorithms. A competitive selection model (multilayer perceptron) is then used to select the output from one of the ensemble members to be the final output of the ensemble model. The ensemble model created by such a stacked generalization is able to achieve extremely high accuracy in predicting the roll separation force with the average relative accuracy being within 1% of the actual measured roll force. ISBN 0889863520 9780889863521 Language eng Field of Research 091099 Manufacturing Engineering not elsewhere classified HERDC Research category E1 Full written paper - refereed Copyright notice ©2005, Monash University Persistent URL http://hdl.handle.net/10536/DRO/DU:30004828 Document type: Conference Paper Collection: School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 18 Sep 2008, 12:19:28 EST Fri, 03 Apr 2009, 10:46:06 EST Fri, 17 Oct 2014, 08:34:31 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 953 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Mon, 07 Jul 2008, 09:41:59 EST

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