Soft fuzzy rough sets and its application in decision making
B Sun, W Ma - Artificial Intelligence Review, 2014 - Springer
B Sun, W Ma
Artificial Intelligence Review, 2014•SpringerRecently, the theory and applications of soft set has brought the attention by many scholars
in various areas. Especially, the researches of the theory for combining the soft set with the
other mathematical theory have been developed by many authors. In this paper, we propose
a new concept of soft fuzzy rough set by combining the fuzzy soft set with the traditional fuzzy
rough set. The soft fuzzy rough lower and upper approximation operators of any fuzzy subset
in the parameter set were defined by the concept of the pseudo fuzzy binary relation (or …
in various areas. Especially, the researches of the theory for combining the soft set with the
other mathematical theory have been developed by many authors. In this paper, we propose
a new concept of soft fuzzy rough set by combining the fuzzy soft set with the traditional fuzzy
rough set. The soft fuzzy rough lower and upper approximation operators of any fuzzy subset
in the parameter set were defined by the concept of the pseudo fuzzy binary relation (or …
Abstract
Recently, the theory and applications of soft set has brought the attention by many scholars in various areas. Especially, the researches of the theory for combining the soft set with the other mathematical theory have been developed by many authors. In this paper, we propose a new concept of soft fuzzy rough set by combining the fuzzy soft set with the traditional fuzzy rough set. The soft fuzzy rough lower and upper approximation operators of any fuzzy subset in the parameter set were defined by the concept of the pseudo fuzzy binary relation (or pseudo fuzzy soft set) established in this paper. Meanwhile, several deformations of the soft fuzzy rough lower and upper approximations are also presented. Furthermore, we also discuss some basic properties of the approximation operators in detail. Subsequently, we give an approach to decision making problem based on soft fuzzy rough set model by analyzing the limitations and advantages in the existing literatures. The decision steps and the algorithm of the decision method were also given. The proposed approach can obtain a object decision result with the data information owned by the decision problem only. Finally, the validity of the decision methods is tested by an applied example.
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