Modelling of Knowledge via Fuzzy Knowledge Unit in a Case of the ERP Systems Upgrade

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F21%3A89427" target="_blank" >RIV/60460709:41110/21:89427 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.3103%2FS0146411620060061" target="_blank" >https://link.springer.com/article/10.3103%2FS0146411620060061</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3103/S0146411620060061" target="_blank" >10.3103/S0146411620060061</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modelling of Knowledge via Fuzzy Knowledge Unit in a Case of the ERP Systems Upgrade

Popis výsledku v původním jazyce

This article is addressed to knowledge modelling and formalization using a fuzzified knowledge unit. The work is based on the system approach to the definition of knowledge units, on the procedural form of knowledge. Fuzzification of knowledge units draws innovation potential from knowledge units with fuzzy linguistic variables and Mamdani fuzzy inference system. Fuzzy knowledge units arise as a join the best properties of the given approaches. The core is the knowledge unit itself comprising the description of a problem and its solution. The typical knowledge unit consists of four elements: X as problem situation, Y as elementary problem, Z as goal of elementary problem solving and Q as solution of elementary problem. A last element of a knowledge unit Q is fuzzified by fuzzy linguistic variable. Steps of fuzzification process are described in the case study Process customization. The discussion unifies the findings from the chapters with results of the case study.

Název v anglickém jazyce

Modelling of Knowledge via Fuzzy Knowledge Unit in a Case of the ERP Systems Upgrade

Popis výsledku anglicky

This article is addressed to knowledge modelling and formalization using a fuzzified knowledge unit. The work is based on the system approach to the definition of knowledge units, on the procedural form of knowledge. Fuzzification of knowledge units draws innovation potential from knowledge units with fuzzy linguistic variables and Mamdani fuzzy inference system. Fuzzy knowledge units arise as a join the best properties of the given approaches. The core is the knowledge unit itself comprising the description of a problem and its solution. The typical knowledge unit consists of four elements: X as problem situation, Y as elementary problem, Z as goal of elementary problem solving and Q as solution of elementary problem. A last element of a knowledge unit Q is fuzzified by fuzzy linguistic variable. Steps of fuzzification process are described in the case study Process customization. The discussion unifies the findings from the chapters with results of the case study.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Automatic Control and Computer Sciences

ISSN

0146-4116

e-ISSN

1558-108X

Svazek periodika

54

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

12

Strana od-do

529-540

Kód UT WoS článku

000607870400006

EID výsledku v databázi Scopus

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