Suitable site selection for a specific purpose is a crucial activity, and of the greatest importance to a project manager. Several methods have been proposed by the research community for effective site selection, but all proposed methods incur high costs. This study explores the combination of a rough set theory approach (RSTA) with Technique for Order Preference by Similarity to Ideal Solutio...

Covering based Rough Sets are an important generalization of Rough Set Theory. Basically, they replace the partition generated from an equivalence relation by a covering. In this context many approximation operators can be defined [16, 26, 27, 28, 34]. In this paper we want to discover relationships among approximation operators defined from neighborhoods. We use the concepts of duality, adjoin...

Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision making. Data mining is a discipline that has an important contribution to data analysis, discovery of new meaningful knowledge, and autonomous decision making. The rough set theory offers a viable approach for decision rule extraction from data.This paper, introduces the fundamental concepts of rou...

module over a ring is a general mathematical concept for many examples of mathematicalobjects that can be added to each other and multiplied by scalar numbers.in this paper, we consider a module over a ring as a universe and by using the notion of reference points, we provide local approximations for  subsets of the universe.

In this paper, two similarity measures are proposed: one for the similarity between rough sets in the classical rough set theory based on indiscernibility relation and the other between rough sets in the extended rough set theory based on limited tolerance relation. The proposed measures can provide a useful way for measuring the degree of similarity between rough sets. Key-words: Rough set; In...

Grouping web transactions into clusters is important in order to obtain better understanding of user’s behavior. Currently, the rough approximation-based clustering technique has been used to group web transactions into clusters. However, the processing time is still an issue due to the high complexity for finding the similarity of upper approximations of a transaction which used to merge betwe...

Rough set theory is one of important tools of soft computing, and rough approximations are the essential elements in rough set models. However, the existing fuzzy rough set model for set-valued data, which is directly constructed based on a kind of similarity relation, fail to explicitly define fuzzy rough approximations. To solve this issue, in this paper, we propose two types of fuzzy rough a...

[ Abstract.] The paper contains some considerations concerning the relationship between decision rules and inference rules from the rough set theory perspective. It is shown that decision rules can be interpreted as a generalization of the modus ponens inference rule, however there is an essential difference between these two concepts. Decision rules in the rough set approach are used to descri...

Web-based learning is gaining popularity due to its convenience, ubiquity, personalization, and adaptation features compared with traditional learning environments. The learning subjects of Web-based learning systems are mostly for popular sciences. Little attention has been paid for learning cutting edge subjects and no such systems have been developed for rough sets. Rough set theory has obta...

For an incomplete information system, attribute reduction is an important problem. To dealing with it, this paper proposed a new attribute reduction method based on information quantity. On one hand, this approach improved traditional tolerance relationship calculation methods using an extension of tolerance relationship in rough set theory. On the other hand, a new method was present for calcu...