Prediction of multi-class industrial data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088855" target="_blank" >RIV/61989100:27240/13:86088855 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/13:86088855
Result on the web
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6630290" target="_blank" >http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6630290</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Prediction of multi-class industrial data
Original language description
Industrial plants use many different sensors for processes monitoring and controlling. These sensors generate huge amount of data. These data should be used for improving of the quality of semi and final products in each factory. In this paper, we describe processing of two different datasets acquired from a steel-mill factory using three different methods SVM, Fuzzy Rules and Bayesian classification. Moreover, we describe problems of each method with confrontation with real data. Each of the method used works in different algorithm and is not based on the same theory. Their comparison gives a nice review of the real application of these methods.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings - 5th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2013
ISBN
978-0-7695-4988-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
64-68
Publisher name
IEEE
Place of publication
Danvers
Event location
Xi'an
Event date
Sep 9, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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