Abstract
In 2011 Alkhazaleh and Salleh introduced the concept of soft expert set and gave an application in a decision‐making problem. In this paper we introduce the concept of fuzzy parameterized soft expert set by giving an important degree for each element in the set of parameters. We also study its properties and define its basic operations, namely, complement, union, intersection, AND, and OR. Finally, we give an application in decision making.
Highlights
Many fields deal with uncertain data that may not be successfully modeled by classical math ematics
An agree-fuzzy parameterized soft expert set (FPSES) F, A D1 over U is an FPSE subset of F, A D where the opinions of all experts are agree and is defined as follows: F, A D1 {FD α : α ∈ D × X × {1}}
A disagree-FPSES F, A D0 over U is an FPSE subset of F, A D where the opinions of all experts are disagree and is defined as follows: F, A D0 {FD α : α ∈ D × X × {0}}
Summary
Many fields deal with uncertain data that may not be successfully modeled by classical math ematics. Molodtsov 1 proposed a completely new approach for modeling vagueness and uncertainty This so-called soft set theory has potential applications in many different fields. Majumdar and Samanta 7 defined and studied the generalised fuzzy soft sets where the degree is attached with the parameterization of fuzzy sets while defining a fuzzy soft set. Zhou et al 8 defined and studied generalised interval-valued fuzzy soft sets where the degree is attached with the parameterization of interval-valued fuzzy sets while defining an interval-valued fuzzy soft set. Alkhazaleh et al 9 defined the concepts of possibility fuzzy soft set and gave their applications in decision making and medical diagnosis. Alkhazaleh and Salleh introduced the concept of a soft expert set, and Alkhazaleh introduced fuzzy soft expert set, where the user can know the opinion of all experts in one model without any operations. We give an application of fuzzy parameterized soft expert set in decision-making problem
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