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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4778

Title: Evolutionary computing for metals properties modelling
Authors: Abbod, MF
Mahfouf, M
Linkens, DA
Sellars, CM
Keywords: Alloy Materials
Genetic Programming
Material Property
Modeling
Strain
Stress
Publication Date: 2007
Publisher: Trans Tech Publications
Citation: Materials Science Forum, 539-543: 2449-2454
Abstract: During the last decade Genetic Programming (GP) has emerged as an efficient methodology for teaching computers how to program themselves. This paper presents research work which utilizes GP for developing mathematical equations for the response surfaces that have been generated using hybrid modelling techniques for predicting the properties of materials under hot deformation. Collected data from the literature and experimental work on aluminium are utilized as the initial training data for the GP to develop the mathematical models under different deformation conditions and compositions.
Description: This is a post print version of the article, the official published version can be obtained from the link below.
Sponsorship: Financial support from the UK EPSRC (Engineering and Physical Sciences Research Council) under grant number GR/R70514/01 was used in this study.
URI: http://bura.brunel.ac.uk/handle/2438/4778
DOI: http://dx.doi.org/10.4028/www.scientific.net/MSF.539-543.2449
ISSN: 0255-5476
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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