Prediction of mechanical property of steel strips using multivariate adaptive regression splines
A. Mukhopadhyay and
A. Iqbal
Journal of Applied Statistics, 2009, vol. 36, issue 1, 1-9
Abstract:
In recent times, the problem of prediction of properties of a steel strip has attracted enormous attention from different communities such as statistics, data mining, soft computing, and engineering. This is due to the prospective benefits of reduction in testing and inventory cost, increase in yield, and improvement in delivery compliance. The complexity of the problem arises due to its dependency on the chemical composition of the steel, and a number of processing parameters. To predict the mechanical properties of the strip (yield strength, ultimate tensile strength, and Elongation), a model based on multivariate adaptive regression spline has been developed. It is found that the prediction agrees well with the actual measured data.
Keywords: data mining; MARS; property prediction; soft computing; statistics; steel (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:36:y:2009:i:1:p:1-9
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DOI: 10.1080/02664760802193252
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