Rough set theory provides a methodology for data analysis based on the approximation of concepts in information systems. It revolves around the notion of discernibility: the ability to distinguish between objects, based on their attribute values. It allows to infer data dependencies that are useful in the fields of feature selection and decision model construction. In many cases, however, it is...

Attribute reduction (feature selection) has become an important challenge in areas of pattern recognition, machine learning, data mining and knowledge discovery. Based on attribute reduction, one can extract fuzzy decision rules from a fuzzy decision table. As consistency is one of several criteria for evaluating the decision performance of a decision-rule set, in this paper, we devote to prese...

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship ...

For the time when we deal with the difficulty of determining a decision attribute among several candidates to find more accurate decision models, we propose a new method to help users find a good decision attribute based on the overall correctness of the target database. The overall correctness is measured by the degree of non-conflicting decisions based on rough set theory. By assessing the me...

-This paper proposes a grey interval relation TOPSIS method for the decision making in which all of the attribute weights and attribute values are given by the interval grey numbers. In this paper, all of the subjective and objective weights are obtained by interval grey number and decision-making is based on four methods such as the relative approach degree of grey TOPSIS, the relative approac...

The paper investigates some similarity measures in interval bipolar neutrosophic environment for multi-attribute decision making problems. At first, we define Hamming and Euclidean distances measures between interval bipolar neutrosophic sets and establish their basic properties. We also propose two similarity measures based on the Hamming and Euclidean distance functions. Using maximum and min...

The article presents an approach to the development of multi-attribute decision making model that is based on DEX, an expert system shell for multi-attribute decision support. We demonstrate the applicability and flexibility of the approach presenting application of DEX in e-learning: assessment and evaluation of Learning Management Systems (LMS) where several conflicting objectives, like envir...

We consider a decision problem where a group of individuals evaluates multiattribute alternatives. We explore the minimal required agreements that are sufficient to specify the group utility function. A surprising result is that, under some conditions, a bilateral agreement among pairs of individuals on a single attribute is sufficient to derive the multiattribute group utility. The bilateral a...