Multiple attribute decision making based on Pythagorean fuzzy Aczel-Alsina average aggregation operators
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73617149" target="_blank" >RIV/61989592:15310/23:73617149 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s12652-022-04360-4?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot" target="_blank" >https://link.springer.com/article/10.1007/s12652-022-04360-4?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s12652-022-04360-4" target="_blank" >10.1007/s12652-022-04360-4</a>
Alternative languages
Result language
angličtina
Original language name
Multiple attribute decision making based on Pythagorean fuzzy Aczel-Alsina average aggregation operators
Original language description
A useful expansion of the intuitionistic fuzzy set (IFS) for dealing with ambiguities in information is the Pythagorean fuzzy set (PFS), which is one of the most frequently used fuzzy sets in data science. Due to these circumstances, the Aczel-Alsina operations are used in this study to formulate several Pythagorean fuzzy (PF) Aczel-Alsina aggregation operators, which include the PF Aczel-Alsina weighted average (PFAAWA) operator, PF Aczel-Alsina order weighted average (PFAAOWA) operator, and PF Aczel-Alsina hybrid average (PFAAHA) operator. The distinguishing characteristics of these potential operators are studied in detail. The primary advantage of using an advanced operator is that it provides decision-makers with a more comprehensive understanding of the situation. If we compare the results of this study to those of prior strategies, we can see that the approach proposed in this study is more thorough, more precise, and more concrete. As a result, this technique makes a significant contribution to the solution of real-world problems. Eventually, the suggested operator is put into practise in order to overcome the issues related to multi-attribute decision-making under the PF data environment. A numerical example has been used to show that the suggested method is valid, useful, and effective.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Ambient Intelligence and Humanized Computing
ISSN
1868-5137
e-ISSN
1868-5145
Volume of the periodical
14
Issue of the periodical within the volume
8
Country of publishing house
DE - GERMANY
Number of pages
15
Pages from-to
10931-10945
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85135832412