2022
DOI: 10.1111/exsy.13196
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Group decision‐making analysis based on distance measures under rough environment

Abstract: A rough set as a superset of a crisp set is a mathematical tool to cope with uncertainty using initial data without additional assumptions and pre-defined parameters.Using the technique of upper and lower approximations, rough models provide a complete description of the problem. This paper aims to introduce the notion of distance function, which is a metric, in rough graphs. We establish formulae of distance function, degree and radius of certain products of rough graphs in terms of initial given rough graphs… Show more

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Cited by 9 publications
(3 citation statements)
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References 33 publications
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“…Akram and Zahid [2] illustrated the extended TOPSIS under a Pythagorean fuzzy rough environment for concept evaluation. Fatima et al [12] discussed the concept of distance function in rough graphs for group decision-making. They also developed formulae for the radius and degree of some rough graph products.…”
Section: Authorsmentioning
confidence: 99%
“…Akram and Zahid [2] illustrated the extended TOPSIS under a Pythagorean fuzzy rough environment for concept evaluation. Fatima et al [12] discussed the concept of distance function in rough graphs for group decision-making. They also developed formulae for the radius and degree of some rough graph products.…”
Section: Authorsmentioning
confidence: 99%
“…A decision model utilizing m-polar fuzzy preference relations was proposed to address multicriteria decision-making challenges. Studying rough approximations of graphs and hypergraphs [11], distance measures in rough environments [12], and decisionmaking based on a color spectrum in rough environments provides an extension of domination features [13]. The computation of domination numbers has been conducted for certain categories of graphs, including sparse graphs [14], grid graphs [15], planar graphs [16], regular graphs [17], bipartite graphs [18], social networks, random geometric graphs, pseudofractal scale-free web graphs [19], wheel graphs [20], neural networks [21], and others [22].…”
Section: Introductionmentioning
confidence: 99%
“…Data intelligence is the practice of utilizing ML to analyse and transform data into actionable insights (Chen et al, 2012). By using this approach, business processes can be improved, better decisions can be made, and future outcomes can be predicted (Fatima et al, 2023; Li, 2022). It is a rapidly growing field, as businesses increasingly use data to their advantage.…”
Section: Introduction and Related Workmentioning
confidence: 99%