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An Adjustable Method for Data Ranking based on Fuzzy Soft Sets
This work deals with an adjustable approach for ranking objects based on fuzzy soft models. We first generate two preorder relations, thus, two equivalence relations based on the fuzzy soft topology. Then, a method for data ranking is designed according to these binary relations. The connection between Separation axioms and such data ranking method is also studied. Finally, an example is provided to illustrate this method for problem of data ranking.
Keywords
Decision Making, Fuzzy Soft Product Topology, Fuzzy Soft Subspace, Fuzzy Soft Topology, Preorder Relation
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