Evidence map›Paper›PMID 38590855›Full record

ArticleHeliyon2024

Cosine and cotangent similarity measures for intuitionistic fuzzy hypersoft sets with application in MADM problem.

Muhammad Naveed Jafar, Muhammad Saeed, Ayesha Saeed, Aleen Ijaz, Mobeen Ashraf, Fahd Jarad

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

6 authors.

Muhammad Naveed JafarDepartment of Mathematics, University of Management and Technology, 54000, Lahore, Pakistan.
Muhammad SaeedDepartment of Mathematics, University of Management and Technology, 54000, Lahore, Pakistan.
Ayesha SaeedDepartment of Mathematics, University of Management and Technology, 54000, Lahore, Pakistan.
Aleen IjazDepartment of Mathematics, University of Management and Technology, 54000, Lahore, Pakistan.
Mobeen AshrafDepartment of Mathematics, University of Management and Technology, 54000, Lahore, Pakistan.
Fahd JaradDepartment of Mathematics, Çankaya University, Etimesgut, 06790, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intuitionistic fuzzy hypersoft sets (IFHSSs) are a novel model that is projected to address the limitations of Intuitionistic fuzzy soft sets (IFSSs) regarding the entitlement of a multi-argument domain for the approximation of parameters under consideration. It is more flexible and reliable as it considers the further classification of parameters into their relevant parametric valued sets. In this paper, we proposed some trigonometric (cosine and cotangent) similarity measures and their weighted trigonometric similarity measures (SMs). Trigonometric Similarity measures (SMs) for intuitionistic fuzzy hypersoft sets (IFHSSs) are significantly implied to check the similarity measures and help to determine the similarity between different factors. Also, in order to evaluate the validity of the significant study and apply the results to a daily life problem. We use them to solve problems involving the selection of renewable energy sources. According to several technical contributing factors, the analysis identifies the ideal location for the implementation of the energy production units. Future case studies with many features and additional bifurcation along with multiple decision-makers can use the suggested methodologies. Also, several existing structures, such as fuzzy, Pythagorean fuzzy, Neutrosophic theories, etc., can be utilized with the suggested method.

Indexed as

CosineCotangentHypersoft sets (HSSs)Intuitionistic fuzzy hypersoft sets (IFH0SSs)Multi-attribute decision making (MADM)Similarity measures (SMs)Soft sets (Ss)

Identifiers

PMID38590855
PMCPMC10999856

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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.