Please use this identifier to cite or link to this item: https://doi.org/2013/362601
Title: Ameliorated austenite carbon content control in austempered ductile irons by support vector regression
Authors: Yang, C.-Y.
Chang, L.-C.
Samani, H.
Nakatsu, R. 
Issue Date: 2013
Source: Yang, C.-Y.,Chang, L.-C.,Samani, H.,Nakatsu, R. (2013). Ameliorated austenite carbon content control in austempered ductile irons by support vector regression. Mathematical Problems in Engineering 2013 : -. ScholarBank@NUS Repository. https://doi.org/2013/362601
Abstract: Austempered ductile iron has emerged as a notable material in several engineering fields, including marine applications. The initial austenite carbon content after austenization transform but before austempering process for generating bainite matrix proved critical in controlling the resulted microstructure and thus mechanical properties. In this paper, support vector regression is employed in order to establish a relationship between the initial carbon concentration in the austenite with austenization temperature and alloy contents, thereby exercising improved control in the mechanical properties of the austempered ductile irons. Particularly, the paper emphasizes a methodology tailored to deal with a limited amount of available data with intrinsically contracted and skewed distribution. The collected information from a variety of data sources presents another challenge of highly uncertain variance. The authors present a hybrid model consisting of a procedure of a histogram equalizer and a procedure of a support-vector-machine (SVM-) based regression to gain a more robust relationship to respond to the challenges. The results show greatly improved accuracy of the proposed model in comparison to two former established methodologies. The sum squared error of the present model is less than one fifth of that of the two previous models. © 2013 Chan-Yun Yang et al.
Source Title: Mathematical Problems in Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/54974
ISSN: 1024123X
DOI: 2013/362601
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