Abstract
Fuzzy rough set theory is a hybrid method that deals with vagueness and uncertainty emphasized in decision-making. In this research study, we apply the concept of fuzzy rough sets to graphs. We introduce the notion of fuzzy rough digraphs and describe some of their methods of construction. In particular, we consider applications of fuzzy rough digraphs. We also present algorithms to solve decision-making problems regarding selection of a city for treatment and identification of best location in a department to set mobile phone Jammer.
Highlights
Fuzzy set theory 23 introduced by Zadeh gives information about how much possibilities are there that an element belongs to the target set determined on the basis of given attribute
Rough set theory was introduced on the assumption that every object of the set is associated with a property
Decision making is very important in our daily life
Summary
Fuzzy set theory 23 introduced by Zadeh gives information about how much possibilities are there that an element belongs to the target set determined on the basis of given attribute. Fuzzy set theory is a single parameter approach. Rough set theory 14 is general mathematical approach. Rough set theory is used when we have a requirement to manipulate data on the basis of set of attributes. Rough set theory was introduced on the assumption that every object of the set is associated with a property. The relation generated on the basis of this similarity is a basic tool in rough set theory. A rough set consists of a pair of lower approximation and an upper approximation (of target set) determined by this relation.
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