Order-α_CQ Divergence Measures and Aggregation Operators Based on Complex q-Rung Orthopair Normal Fuzzy Sets and Their Application to Multi-Attribute Decision-Making

Authors

Zeeshan Ali¹, Tahir Mahmood^1, , Abdu Gumaei^{2, *,}

¹Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan

²STC's Artificial Intelligence Chair, Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

^*Corresponding author: Email: agumaei.c@ksu.edu.sa

DOI

10.2991/ijcis.d.210622.004How to use a DOI?

Keywords

Complex q-Rung orthopair normal fuzzy sets; Order-αCQ divergence measures; Aggregation operators; Multi-attribute decision-making

Abstract

Complex q-rung orthopair fuzzy set (CQROFS) contains the grade of supporting and the grade of supporting against in the form of polar coordinates belonging to unit disc in a complex plane and is a proficient technique to address awkward information, although the normal fuzzy number (NFN) examines normal distribution information in anthropogenic action and a realistic environment. Based on the advantages of both notions, in this manuscript, we explored the novel concept of a complex q-rung orthopair normal fuzzy set (CQRONFS) as an imperative technique to evaluate unreliable and complicated information. Some operational laws based on CQRONFSs are also explored. Additionally, some distance measures, called complex q-rung orthopair normal fuzzy generalized distance measure (CQRONFGDM), complex q-rung orthopair normal fuzzy symmetric distance measure (CQROFNFSDM), two types of complex q-rung orthopair normal fuzzy order- divergence measures (CQRONFODMs), and their special cases are discussed. Moreover, weighted averaging, weighted geometric, generalized weighted averaging, and generalized weighted geometric operators based on CQRONFSs are also presented. In last, we solved a numerical example of a multi-attribute decision-making (MADM) problem is shown to justify the proficiency of the presented operators. The advantages, comparative and sensitive analyses are used to express the efficiency and flexibility of the explored approach.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Zeeshan Ali
AU  - Tahir Mahmood
AU  - Abdu Gumaei
PY  - 2021
DA  - 2021/07/01
TI  - Order-αCQ Divergence Measures and Aggregation Operators Based on Complex q-Rung Orthopair Normal Fuzzy Sets and Their Application to Multi-Attribute Decision-Making
JO  - International Journal of Computational Intelligence Systems
SP  - 1895
EP  - 1922
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210622.004
DO  - 10.2991/ijcis.d.210622.004
ID  - Ali2021
ER  -