Transfer-stable aggregation functions: Applications, challenges, and emerging trends
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F23%3A63561738" target="_blank" >RIV/70883521:28140/23:63561738 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2772662223000504?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2772662223000504?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.dajour.2023.100210" target="_blank" >10.1016/j.dajour.2023.100210</a>
Alternative languages
Result language
angličtina
Original language name
Transfer-stable aggregation functions: Applications, challenges, and emerging trends
Original language description
The original transfer-stable aggregation functions generalized the arithmetic means to finite chains. The idea of applying these functions was later demonstrated by purchasing several products depending on the quality and price of the products. This paper aims to continue this idea and show other possible applications of transfer-stable aggregation functions. We identify several concerns in various applications and present possible remedies to address these concerns. We show different types of lattices could be used to compile the assignment of a given application problem. Based on this finding, we can very effectively divide the products into so-called qualitative classes. We conclude that distance-stable lattices are most effective in these applications. Moreover, we also show that the classes better reflect reality using these lattices.
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
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
Decision Analytics Journal
ISSN
2772-6622
e-ISSN
2772-6622
Volume of the periodical
2023
Issue of the periodical within the volume
7
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
1-16
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85151407807