Evaluation of Stream Data by Formal Concept Analysis
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86093048" target="_blank" >RIV/61989100:27240/13:86093048 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Evaluation of Stream Data by Formal Concept Analysis
Popis výsledku v původním jazyce
Following article presents practical usage of the Formal Concept Analysis (FCA) for the evaluation of stream data recorded during a technological process. The main aim of this paper is to show possibilities of using FCA to detect anomalies in the data. Our attitude is based on the fact that although during the production process a large amount of input data is obtained, the size of conceptual lattice is relatively small, and therefore, it is possible to work with it in real-time. The conceptual latticerepresents a model of production process, and this model is based on historical production data. The input data stream contains measurements on the production line and it is applied on the model of the production process. The result of this activity is to identify anomalies in the incoming data and their relationship with faulty products, including disclosure of possible causes of errors and also to obtain a histogram of quality for manufactured products.
Název v anglickém jazyce
Evaluation of Stream Data by Formal Concept Analysis
Popis výsledku anglicky
Following article presents practical usage of the Formal Concept Analysis (FCA) for the evaluation of stream data recorded during a technological process. The main aim of this paper is to show possibilities of using FCA to detect anomalies in the data. Our attitude is based on the fact that although during the production process a large amount of input data is obtained, the size of conceptual lattice is relatively small, and therefore, it is possible to work with it in real-time. The conceptual latticerepresents a model of production process, and this model is based on historical production data. The input data stream contains measurements on the production line and it is applied on the model of the production process. The result of this activity is to identify anomalies in the incoming data and their relationship with faulty products, including disclosure of possible causes of errors and also to obtain a histogram of quality for manufactured products.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2013
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Advances in Intelligent Systems and Computing
ISBN
978-3-642-32517-5
ISSN
2194-5357
e-ISSN
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Počet stran výsledku
10
Strana od-do
131-140
Název nakladatele
Springer
Místo vydání
Heidelberg
Místo konání akce
Poznaň
Datum konání akce
17. 9. 2012
Typ akce podle státní příslušnosti
EUR - Evropská akce
Kód UT WoS článku
000312972300013