Evidence map›Paper›PMID 41833945›Full record

ArticleScientific reports2026

A novel complex Fermatean fuzzy formalism with improved score function and aggregation operators.

Abdul Razaq, Laiba Komal, Ghaliah Alhamzi, Abdul Wakil Baidar

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Abdul RazaqDepartment of Mathematics, Division of Science and Technology, University of Education, Lahore, 54770, Pakistan.
Laiba KomalDepartment of Mathematics, Division of Science and Technology, University of Education, Lahore, 54770, Pakistan.
Ghaliah AlhamziDepartment of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), 11564, Riyadh, Saudi Arabia. gyalhamzi@imamu.edu.sa.
Abdul Wakil BaidarDepartment of Mathematics, Kabul University, Kabul, Afghanistan. baidarmath87@ku.edu.af.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of intelligent systems and data-driven technologies, making precise and reliable decisions under uncertainty has become increasingly vital. The primary aim of this study is to tackle decision making (DM) issues by developing the technique of aggregation operators (AOs) within a complex Fermatean fuzzy (CFF) environment. A novel score function is defined to resolve the shortcomings of the existing score function for complex Fermatean fuzzy numbers (CFFNs). We introduce two novel ordered weighted aggregation operators: the complex Fermatean fuzzy ordered weighted averaging (CFFOWA) operator and the complex Fermatean fuzzy ordered weighted geometric (CFFOWG) operator. Furthermore, the study explores many important features of the proposed operators. The updated score function and proposed operators (CFFOWA and CFFOWG) are successfully employed to select the most optimal signal processing and communication system for better traffic control. Finally, a comparative analysis is performed to illustrate the reliability and efficacy of the proposed methods relative to existing methodologies. The study contributes to the field of assessment and decision-making by offering innovative and efficient tools and methodologies.

Indexed as

Aggregation operatorsComplex fermatean fuzzy setMulti-attribute decision making (MADM)Signal processing

Identifiers

PMID41833945
PMCPMC13121620

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.