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Research Article | Open Access

Logarithmic cubic aggregation operators and their application in online study effect during Covid-19

Muhammad Qiyas1Muhammad Naeem2( ) Muneeza1 Arzoo3
Department of Mathematics, Abdul Wali Khan University Mardan, Mardan, KP, Pakistan
Department of Mathematics Deanship of Applied Sciences Umm Al-Qura University, Makkah, Saudi Arabia
Department of Mathematics, Government Postgraduate College for Women Mardan, KP, Pakistan
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Abstract

The aims of this study is to define a cubic fuzzy set based logarithmic decision-making strategy for dealing with uncertainty. Firstly, we illustrate some logarithmic operations for cubic numbers (CNs). The cubic set implements a more pragmatic technique to communicate the uncertainties in the data to cope with decision-making difficulties as the observation of the set. In fuzzy decision making situations, cubic aggregation operators are extremely important. Many aggregation operations based on the algebraic t-norm and t-conorm have been developed to cope with aggregate uncertainty expressed in the form of cubic sets. Logarithmic operational guidelines are factors that help to aggregate unclear and inaccurate data. We define a series of logarithmic averaging and geometric aggregation operators. Finally, applying cubic fuzzy information, a creative algorithm technique for analyzing multi-attribute group decision making (MAGDM) problems was proposed. We compare the suggested aggregation operators to existing methods to prove their superiority and validity, and we find that our proposed method is more effective and reliable as a result of the comparison and sensitivity analysis.

CLC number: 03E72, 47S40

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AIMS Mathematics
Pages 5847-5878

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Cite this article:
Qiyas M, Naeem M, Muneeza, et al. Logarithmic cubic aggregation operators and their application in online study effect during Covid-19. AIMS Mathematics, 2023, 8(3): 5847-5878. https://doi.org/10.3934/math.2023295

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Received: 24 September 2022
Revised: 10 December 2022
Accepted: 12 December 2022
Published: 15 March 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)