lfl: An R Package for Linguistic Fuzzy Logic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F22%3AN23026CR" target="_blank" >RIV/61988987:17610/22:N23026CR - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0165011421002475?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0165011421002475?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.fss.2021.07.007" target="_blank" >10.1016/j.fss.2021.07.007</a>

Jazyk výsledku

angličtina

Název v původním jazyce

lfl: An R Package for Linguistic Fuzzy Logic

Popis výsledku v původním jazyce

This paper presents an R package that supports the use of fuzzy relational calculus and linguistic fuzzy logic in data processing applications. Thelflpackage enables computing compositions of fuzzy relations enhanced with distinct extensions, such as excluding features, unavoidable features, or generalized quantifiers. Furthermore, it provides tools for transformation of data into fuzzy sets representing linguistic expressions, mining of linguistic fuzzy association rules, and performing an inference on fuzzy rule bases using the Perception-based logical deduction (PbLD). The package also enables to use the Fuzzy rule-based ensemble, a tool for time series forecasting based on an ensemble of forecasts from several individual methods implemented in R. To the best of the authors’ knowledge, there is no other open source software that would provide free tools covering the above-described fragments of the fuzzy modeling area. Therefore, we find highly desirable to allow the community to get familiar with the tools as well as their implementation.

Název v anglickém jazyce

lfl: An R Package for Linguistic Fuzzy Logic

Popis výsledku anglicky

This paper presents an R package that supports the use of fuzzy relational calculus and linguistic fuzzy logic in data processing applications. Thelflpackage enables computing compositions of fuzzy relations enhanced with distinct extensions, such as excluding features, unavoidable features, or generalized quantifiers. Furthermore, it provides tools for transformation of data into fuzzy sets representing linguistic expressions, mining of linguistic fuzzy association rules, and performing an inference on fuzzy rule bases using the Perception-based logical deduction (PbLD). The package also enables to use the Fuzzy rule-based ensemble, a tool for time series forecasting based on an ensemble of forecasts from several individual methods implemented in R. To the best of the authors’ knowledge, there is no other open source software that would provide free tools covering the above-described fragments of the fuzzy modeling area. Therefore, we find highly desirable to allow the community to get familiar with the tools as well as their implementation.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/GA20-07851S" target="_blank" >GA20-07851S: Fuzzy relační struktury v přibližném usuzování</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

FUZZY SET SYST

ISSN

0165-0114

e-ISSN

—

Svazek periodika

—

Číslo periodika v rámci svazku

03/2022

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

38

Strana od-do

1-38

Kód UT WoS článku

000759790100001

EID výsledku v databázi Scopus

2-s2.0-85111796002