Abstract In this paper, we introduce a topological method to produce new rough set models. This is based on the idea of “somewhat open sets” which one celebrated generalizations sets. We first generate some topologies from different types $$N_\rho $$ N ρ -neighborhoods....

Three computer algorithms are presented. One reduces a network N to its interior, I. Another counts all the triangles in network, and last randomly generates networks similar given just interior However, these not usual numeric programs that manipulate matrix representation of network; they set-based. Union meet essential binary operators; contained_in is basic relational comparator. The I show...

In this paper, we propose a dominance-based rough set approach for the decision analysis of a preference-ordered uncertain data table, which is comprised of a finite set of objects described by a finite set of criteria. The domains of the criteria may have ordinal properties that express preference scales. In the proposed approach, we first compute the degree of dominance between any two object...

Rough Set Theory is a fairly new concept that has found applications to various soft computing techniques. It offers a set theory approach to manage the uncertainty in data systems. It has been used for the discovery of data dependencies, importance of features, patterns in sample data, feature space dimensionality reduction, and the classification of objects. Objects can be classified by means...

This paper aims at combining variable ordering structures with set relations in set optimization, which have been defined using the constant ordering cone before. Since the purpose is to connect these two important approaches in set optimization, we do not restrict our considerations to one certain relation. Conversely, we provide the reader with many new variable set relations generalizing the...