Grey dominance variable precision rough set model based on grey dominance relationship

Abstract

Purpose – The purpose of this paper is to construct a novel grey dominance variable precision rough model. Design/methodology/approach – To deal with the problems that the attribute values of the decision-making object are often not exact numbers but interval grey numbers, and the decision-making attributes satisfy a certain preference relationship in the decision-making information because of the complexity and uncertainty of the real world, the authors take advantage of the theoretical thinking of the grey systems, dominance rough set theory and variable precision rough set theory, and construct a novel dominance variable precision rough set model. On the basis of the thinking logic of grey systems, the authors first define the concepts of balance degree, dominance degree and inferior degree, and then the grey dominance relationship based on the comparison of interval grey numbers. Then the authors use the grey dominance relationship to substitute for the indiscernibility relationship of the variable precision rough set so that the grey dominance variable precision rough model is naturally utilized to reduce the system's attributes in order to derive the needed decision rules. At the end, the authors use a decision-making example of the radar target selection to demonstrate the feasibility and effectiveness of the novel model. Findings – The results show that the proposed model possesses certain fault tolerance ability and can well-realize decision rule extraction and knowledge discovery out of a given incomplete information system. Practical implications – The method exposed in the paper can be used to deal with the decision-making problems with the grey information, preference information and noise data. Originality/value – The paper succeeds in realizing both the grey decision-making information with preference information and noise data and the extraction of decision-making rules.