Title :
Application of rough sets for engineering materials classification
Author :
Doreswamy ; Hemanth, K.S. ; Astrad, Channabasayy A M V
Author_Institution :
Dept. of Comput. Sci., Mangalore Univ., Konaje, India
Abstract :
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.
Keywords :
computational linguistics; fuzzy set theory; pattern classification; production engineering computing; rough set theory; engineering materials classification; fuzzy trapezoidal function; inconsistent linguistic data; linguistic value; material class; materials data set; noisy linguistic data; rough set classifier; rough set theory; Adaptation model; Ceramics; Graph theory; IP networks; Metals; Polymers; Decision rule; Engineering Material; Materials Classification; Rough set;
Conference_Titel :
Information Networking and Automation (ICINA), 2010 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-8104-0
Electronic_ISBN :
978-1-4244-8106-4
DOI :
10.1109/ICINA.2010.5636530
