How to Enhance, Use and Understand Fuzzy Relational Compositions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F20%3AA2101MY8" target="_blank" >RIV/61988987:17610/20:A2101MY8 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-31041-7_7" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-31041-7_7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-31041-7_7" target="_blank" >10.1007/978-3-030-31041-7_7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

How to Enhance, Use and Understand Fuzzy Relational Compositions

Popis výsledku v původním jazyce

This article focuses on fuzzy relational compositions, that unquestionably played a crucial role in fundamentals of fuzzy mathematics since the very beginning of their development. We followthe original works aiming at medical diagnosis, where the compositions were actually used for a sort of classification and/or pattern recognition based on expert knowledge stored in the used fuzzy relations. We provide readers with short repetition of theoretical foundations and two recent extensions of the compositions and then, we introduce how they may be combined together. No matter the huge potential of the original compositions and their extensions, if the features are constructed in a certain specific yet very natural way, some limitations for the applicability may be encountered anyhow. This will be demonstrated on a real classification example from biology. The proposedcombinations of extensions will be also experimentally evaluated and they will show the potential for further improvements.

Název v anglickém jazyce

How to Enhance, Use and Understand Fuzzy Relational Compositions

Popis výsledku anglicky

This article focuses on fuzzy relational compositions, that unquestionably played a crucial role in fundamentals of fuzzy mathematics since the very beginning of their development. We followthe original works aiming at medical diagnosis, where the compositions were actually used for a sort of classification and/or pattern recognition based on expert knowledge stored in the used fuzzy relations. We provide readers with short repetition of theoretical foundations and two recent extensions of the compositions and then, we introduce how they may be combined together. No matter the huge potential of the original compositions and their extensions, if the features are constructed in a certain specific yet very natural way, some limitations for the applicability may be encountered anyhow. This will be demonstrated on a real classification example from biology. The proposedcombinations of extensions will be also experimentally evaluated and they will show the potential for further improvements.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications

ISBN

978-3-030-31040-0

Počet stran výsledku

16

Strana od-do

121-136

Počet stran knihy

649

Název nakladatele

Springer

Místo vydání

Cham

Kód UT WoS kapitoly

—