Application of rough sets for engineering materials classification

In this paper, a method of rough set approach to materials data set is presented to predicate material classes using inconsistent values in data set. Material data sets have linguistic values. When these linguistic values are normalized using the fuzzy trapezoidal function, at that time, some information become inconsistent that are indistinguishable by attributes of the dataset. So to overcome this problem we adapted rough set theory to propose a system that reduces the complexity in inconsistent data and offers conditions to consequential analysis. Finally, the experimental results show that the rough set classifier is feasible and effective on noisy and inconsistent linguistic data.