Evidence map›Paper›PMID 35035018›Full record

ArticleArtificial intelligence review2022

Group decision-making with Fermatean fuzzy soft expert knowledge.

Muhammad Akram, Ghous Ali, José Carlos R Alcantud, Aneesa Riaz

Abstract read
In one paragraph

Article in Artificial intelligence review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Muhammad AkramDepartment of Mathematics, University of the Punjab, New Campus, Lahore, Pakistan.ORCID 0000-0001-7217-7962
Ghous AliDepartment of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan.ORCID 0000-0001-5316-3063
José Carlos R AlcantudBORDA Research Unit and IME, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-4533-9281
Aneesa RiazDepartment of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid growth of population, the global impact of solar technology is increasing by the day due to its advantages over other power production technologies. Demand for solar panel systems is soaring, thus provoking the arrival of many new manufacturers. Sale dealers or suppliers face an uncertain problem to choose the most adequate technological solution. To effectively address such kind of issues, in this paper we propose the Fermatean fuzzy soft expert set model by combining Fermatean fuzzy sets and soft expert sets. We describe this hybrid model with numerical examples. From a theoretical standpoint, we demonstrate some essential properties and define operations for this setting. They comprise the definitions of complement, union and intersection, the OR operation and the AND operation. Concerning practice in this new environment, we provide an algorithm for multi-criteria group decision making whose productiveness and authenticity is dutifully tested. We explore a practical application of this approach (that is, the selection of a suitable brand of solar panel system). Lastly, we give a comparison of our model with certain related mathematical tools, including fuzzy and intuitionistic fuzzy soft expert set models.

Indexed as

AlgorithmFermatean fuzzy soft expert setMCGDMSolar panel system

Identifiers

PMID35035018
PMCPMC8742905

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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.