Modelling of Knowledge via Fuzzy Knowledge Unit in a Case of the ERP Systems Upgrade
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F20%3A84766" target="_blank" >RIV/60460709:41110/20:84766 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/article/10.3103/S0146411620060061" target="_blank" >https://link.springer.com/article/10.3103/S0146411620060061</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3103/S0146411620060061" target="_blank" >10.3103/S0146411620060061</a>
Alternativní jazyky
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.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Automatic Control and Computer Sciences
ISSN
1558-108X
e-ISSN
1558-108X
Svazek periodika
54
Číslo periodika v rámci svazku
6
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
12
Strana od-do
529-540
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85099365784