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Identification of desalination and wind power plants sites using m-polar fuzzy Aczel–Alsina aggregation information

Authors :
Zia Ur Rahman
Ghous Ali
Muhammad Asif
Yufeng Chen
Muhammad Zain Ul Abidin
Source :
Scientific Reports, Vol 14, Iss 1, Pp 1-22 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract Real-world decision-making problems often include multi-polar uncertainties dependent on multi-dimensional attributes. The m-polar fuzzy (mF) sets can efficiently handle such multi-faceted complications with T-norm based weighted aggregation techniques. The Aczel–Alsina T-norms offer comparatively flexible and accurate aggregation than the other well-known T-norm families. Consequently, this work introduced novel mF Aczel–Alsina aggregation operators (AOs), including weighted averaging (mFAAWA, mFAAOWA, mFAAHWA) and weighted geometric (mFAAWG, mFAAOWG, mFAAHWG) AOs. The fundamental properties, including boundedness, idempotency, monotonicity, and commutativity are investigated. Based on the proposed AOs, a decision-making algorithm is developed and implemented to solve two detailed multi-polar site selection problems (for desalination plant and for wind-power plant). Finally, a comparison with mF Dombi and mF Yager AOs reveals that different T-norm based AOs may yeild different solutions for the same problem.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322 and 64745341
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.3ddc647453414fc5bfcd182233091ae7
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-023-50397-6