Comparative Study of Clustering Performance by Means of Evolutionary Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F10%3A63509050" target="_blank" >RIV/70883521:28140/10:63509050 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Comparative Study of Clustering Performance by Means of Evolutionary Algorithms
Original language description
Evolutionary algorithms are addressed in many disciplines. These algorithms represent robust adaptive search techniques which can reveal unknown and unexpected relations within inspected data set. More often they are used in data mining methods. The aimof this paper is to compare several widely-used evolutionary algorithms in clustering representing one of data mining method ? specifically the Differential Evolution, SOMA and the Genetic Algorithm. We describe the process of clustering by means of theevolutionary optimization.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Internet, bezpečnost a konkurenceschopnost organizací. Řízení procesů a využití moderních teerminálových technologií
ISBN
978-83-61645-16-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
Univerzita Tomáše Bati ve Zlíně, Fakulta aplikované informatiky
Place of publication
Zlín
Event location
Zlín
Event date
Jan 1, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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