Evolutionary Computing for Metals Properties Modelling

Abstract:

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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.

Info:

Periodical:

Materials Science Forum (Volumes 539-543)

Main Theme:

Edited by:

T. Chandra, K. Tsuzaki, M. Militzer , C. Ravindran

Pages:

2449-2454

DOI:

10.4028/www.scientific.net/MSF.539-543.2449

Citation:

M. F. Abbod et al., "Evolutionary Computing for Metals Properties Modelling", Materials Science Forum, Vols. 539-543, pp. 2449-2454, 2007

Online since:

March 2007

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Price:

$38.00

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[5] Zhu, Q., M.F. Abbod, J. Talamantes-Silva, C.M. Sellars, D.A. Linkens and J.H. Beynon: Hybrid modeling of aluminum-magnesium alloys during thermomechanical processing in terms of physically-based, neuro-fuzzy and finite elements models", Acta Mat, Vol 51 (2003).

DOI: 10.1016/s1359-6454(03)00353-7

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