Confidence Levels-Based <i>p</i>, <i>q</i>-Quasirung Orthopair Fuzzy Operators and Its Applications to Criteria Group Decision Making Problems-Reference-Cited by-同舟云学术

Confidence Levels-Based p, q-Quasirung Orthopair Fuzzy Operators and Its Applications to Criteria Group Decision Making Problems

Published:2023 Issue: Volume:11 Page:109983-109996
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rahim Muhammad¹^ORCID,Shah Kamal²^ORCID,Abdeljawad Thabet²^ORCID,Aphane Maggie³,Alburaikan Alhanouf⁴,Khalifa Hamiden Abd El-Wahed⁴

Affiliation:

1. Department of Mathematics, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan

2. Department of Mathematics and Sciences, Prince Sultan University, Riyadh, Saudi Arabia

3. Department of Mathematics and Applied Mathematics, School of Science and Technology, Sefako Makgatho Health Sciences University, Ga-Rankuwa, South Africa

4. Department of Mathematics, College of Science and Arts, Qassim University, Al Badayea, Saudi Arabia

Funder

Prince Sultan University through the Theoritical and Applied Sciences (TAS) Research Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10271277.pdf?arnumber=10271277

Reference34 articles.

1. Some q-rung orthopair fuzzy Hamacher aggregation operators and their application to multiple attribute group decision making with modified EDAS method

2. Power Aggregation Operators and VIKOR Methods for Complex q-Rung Orthopair Fuzzy Sets and Their Applications

3. A New Generalized Pythagorean Fuzzy Information Aggregation Using Einstein Operations and Its Application to Decision Making

4. Group decision-making analysis based on linguistic q-rung orthopair fuzzy generalized point weighted aggregation operators

5. Novel q-rung orthopair fuzzy interaction aggregation operators and their application to low-carbon green supply chain management

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