Some $$p,q$$ p , q -cubic quasi-rung orthopair fuzzy operators for multi-attribute decision-making

Autor: Yu-Ming Chu, Harish Garg, Muhammad Rahim, Fazli Amin, Asim Asiri, Eskandar Ameer
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Complex & Intelligent Systems, Vol 10, Iss 1, Pp 87-110 (2023)
Druh dokumentu: article
ISSN: 2199-4536
2198-6053
DOI: 10.1007/s40747-023-01092-6
Popis: Abstract This paper aims to support decision-makers improve their ability to accurately capture and represent their judgment in a wide range of situations. To do this, we propose a new type of fuzzy set called a $$p,q$$ p , q -cubic quasi-rung orthopair fuzzy set ( $$p,q$$ p , q -CQOFS). The $$p,q$$ p , q -CQOFS allows for a more flexible and detailed expression of incomplete information through the use of an additional parameter. The paper describes the concept of $$p,q$$ p , q -CQOFS and its relationship to other types of fuzzy sets, introduces score and accuracy functions for $$p,q$$ p , q -CQOFS and analyzes some of its mathematical properties, defines the Hamming distance measure between two $$p,q$$ p , q -CQOFSs and examines some of its important properties, investigates the basic operations of $$p,q$$ p , q -CQOFSs and extends these laws to aggregation operators, and introduces weighted averaging and geometric aggregation operators for combining $$p,q$$ p , q -cubic quasi-rung orthopair fuzzy data.
Databáze: Directory of Open Access Journals
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