The discretization of continuous attributes in a dataset is an essential step before the Rough-Set-Theory (RST)-based classification process applied. There are many methods for discretization, but not them have linked RST instruments from beginning process. objective this research to propose method improve accuracy and reliability RST-based classifier model by involving at In proposed method, k...

Application of intelligent methods in industry become a very challenging issue nowadays and will be of extreme importance in the future. Intelligent methods include, fuzzy sets neural networks genetics algorithms and others techniques known as soft computing. No doubt rough set theory can also contribute essentially to this domain. In this paper basic ideas of rough set theory are presented and...

In this paper, three types of (philosophical, optimistic and pessimistic) multigranulation single valued neutrosophic (SVN) covering-based rough set models are presented, and these three models are applied to the problem of multi-criteria group decision making (MCGDM).Firstly, a type of SVN covering-based rough set model is proposed.Based on this rough set model, three types of mult...