Composition Models of Fuzzy Relations Considering Importance Levels of Features

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F22%3AA2302G9D" target="_blank" >RIV/61988987:17610/22:A2302G9D - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9953776" target="_blank" >https://ieeexplore.ieee.org/document/9953776</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/KSE56063.2022.9953776" target="_blank" >10.1109/KSE56063.2022.9953776</a>

Result language
angličtina
Original language name
Composition Models of Fuzzy Relations Considering Importance Levels of Features
Original language description
Several fuzzy concepts are involved in relational databases such as the degree of fulfilment of a graded property, the level of importance (or of possibility) of a component in a query, grouping features, or the concept of fuzzy quantifiers. We have recently approached the concepts of excluding features and unavoidable features to construct the extensions of fuzzy relational compositions. The extended compositions include the employment of fuzzy quantifiers as well. In this work, we approach the concept of importance levels of considered features in a particular sense that is intuitively suitable to the classification tasks. Then we propose a direction of incorporating this concept into the existing fuzzy relational compositions. We provide various useful properties related to the new models of the compositions. Furthermore, a simple example of the classification of animals in biology is addressed for the behaviour illustration of the proposed models. Finally, we examine the applicability of the new models to the practical application of the Dragonfly classification, which has been considered previously.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
The 2022 14th International Conference on Knowledge and Systems Engineering (KSE)
ISBN
978-1-6654-5281-6
ISSN
2164-2508
e-ISSN
2694-4804
Number of pages
6
Pages from-to
1-6
Publisher name
IEEE
Place of publication
Nha Trang
Event location
Nha Trang
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)