A Comparative Study of Some Soft Rough Sets
Type of publication: International Journal
Year of publication: 2017
Authors: Yaya Liu
Director: Luis Martínez, Keyun Qin
Type: Symmetry
Issue: 11
Volumen: 9
Number: 252
ISSN number: 2073-8994
Abstract: Through the combination of different types of sets such as fuzzy sets, soft sets and rough sets, abundant hybrid models have been presented in order to take advantage of each other and handle uncertainties. A comparative study of relationships and interconnections of some existing hybrid models has been carried out. Some foundational properties of modified soft rough sets (MSR sets) are analyzed. It is pointed out that MSR approximation operators are some kinds of Pawlak approximation operators, whereas approximation operators of Z-soft rough fuzzy sets are equivalent to approximation operators of rough fuzzy sets. The relationships among F-soft rough fuzzy sets, M-soft rough fuzzy sets and Z-soft rough fuzzy sets are surveyed. A new model called soft rough soft sets has been provided as the generalization of F-soft rough sets, and its application in group decision-making has been studied. Various soft rough sets models show great potential as a tool to solve decision-making problems, and a depth study of the connections among these models contributes to the flexible application of soft rough sets based decision-making approaches.
URL: http://www.mdpi.com/2073-8994/9/11/252
DOI: 10.3390/sym9110252