Title of article :
Prediction of mechanical property of steel strips using multivariate adaptive regression splines
Author/Authors :
A. Mukhopadhyay & A. Iqbal، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
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 :
Steel , DATA MINING , Property prediction , Soft computing , statistics , Mars
Journal title :
JOURNAL OF APPLIED STATISTICS
Journal title :
JOURNAL OF APPLIED STATISTICS