Case study for hospital-based Post-Acute Care-Cerebrovascular Disease using Sine Hyperbolic q-rung orthopair fuzzy Dombi aggregation operators. (1st April 2023)

• Record Type: Journal Article
• Authors: Qiyas, Muhammad; Abdullah, Saleem; Khan, Neelam; Naeem, Muhammad; Khan, Faisal; Liu, Yi
• Is Part Of: Expert systems with applications. Volume 215(2023)
• Publication Date: 2023-04-01
• Subjects: q-rung orthopair fuzzy sets -- Sine Hyperbolic q-rung orthopair fuzzy numbers -- Dombi operations -- Sin Hyperbolic q-rung orthopair fuzzy Dombi aggregation operators; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.119224
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: The Sine Hyperbolic q-rung orthopair fuzzy sets ( sinh -q-ROFSs) are the important concept of accepting more uncertainty than the q-rung orthopair fuzzy sets (q-ROFSs). The well-known sine hyperbolic function preserves the origin's periodicity and symmetric existence, and so fulfills the expert's expectations for the multi-time process' parameters. The aim of this study is to offer some robust sine hyperbolic Dombi operation laws ( sinh DOLs) for q-ROFSs in order to preserve these qualities and the significance of sinh -q-ROFSs. Score and accuracy functions for the sinh -q-ROFSs' are also defined. We define a number of new averaging/geometric aggregation operators (AOs) based on Dombi t-norm and conorm operations. The fundamental properties of the defined operators were discussed. Then, using defined AOs, we provide a group decision-making (DM) approach for solving DM problems. We demonstrate a numerical example to verify the defined method. Highlights: We develop a new approach to fuzzy set which is called Sine Hyperbolic q-rung orthopair fuzzy sets. The sine hyperbolic Dombi aggregation operators. The fundamental properties of the defined aggregation operators. Develop a decision making models based on proposed aggregation operators. The comparison analysis show the effective and reliability of the proposed model.