Evidence map›Paper›PMID 38622187›Full record

ArticleScientific reports2024

Selecting an optimal approach to reduce energy crises under interval-valued intuitionistic fuzzy environment.

Dilshad Alghazzawi, Hanan Alolaiyan, Humaira Ashfaq, Umer Shuaib, Hamiden Abd El-Wahed Khalifa, Heba Ghareeb Gomaa, Qin Xin

Abstract read
In one paragraph

Article in Scientific reports, 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

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

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

7 authors.

Dilshad AlghazzawiDepartment of Mathematics, College of Science & Arts, King Abdul Aziz University, Rabigh, Saudi Arabia.
Hanan AlolaiyanDepartment of Mathematics, College of Science, King Saud University, Riyadh, Saudi Arabia.
Humaira AshfaqDepartment of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
Umer ShuaibDepartment of Mathematics, Government College University, Faisalabad, 38000, Pakistan. mumershuaib@gcuf.edu.pk.
Hamiden Abd El-Wahed KhalifaDepartment of Mathematics, College of Science, Qassim University, Buraydah, 51452, Saudi Arabia.
Heba Ghareeb GomaaInstitute for Management Information Systems, Suez, Egypt.
Qin XinFaculty of Science and Technology, University of the Faroe Islands, Vestara Bryggja 15, FO 100 Torshavn, Faroe Islands, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The concept of interval-valued intuitionistic fuzzy sets is intellectually stimulating and holds significant utility in the representation and analysis of real-world problems. The development of similarity measures within the class of interval-valued intuitionistic fuzzy sets possesses significant importance across various academic disciplines, particularly in the fields of decision-making and pattern recognition. The utilization of similarity measures is of utmost importance in the decision-making process when implementing interval-valued intuitionistic fuzzy sets. This is due to its inherent capability to quantitatively assess the level of resemblance or similarity between two interval-valued intuitionistic fuzzy sets. In this article, the drawbacks of the existing similarity measures in the context of an interval-valued intuitionistic fuzzy environment are addressed, and a novel similarity measure is presented. Many fundamental properties of this new interval-valued intuitionistic fuzzy similarity measure are also established, and the effectiveness of this similarity measure is illustrated by presenting a useful example. Moreover, a comparison is given to demonstrate the validity of the newly proposed similarity measure within the existing knowledge of similarity measures in the interval-valued intuitionistic fuzzy environment. In addition, an algorithm is designed to solve multi-criteria decision making problems by means of the proposed measure in the interval-valued intuitionistic fuzzy setting. Furthermore, this newly defined similarity measure is successfully applied to select an optimal renewable energy source to reduce energy crises. Finally, we conduct a comparative study to showcase the authenticity of the recently defined technique within the existing knowledge of similarity measures in the interval-valued intuitionistic fuzzy environment.

Indexed as

Decision makingInterval valued intuitionistic fuzzy setOptimizationRenewable energy sourceSimilarity measure

Identifiers

PMID38622187
PMCPMC11018613

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.