Maximizing vector distances using differential evolution - Relation to data redundancy

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F15%3A43874253" target="_blank" >RIV/70883521:28140/15:43874253 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1063/1.4912774" target="_blank" >http://dx.doi.org/10.1063/1.4912774</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/1.4912774" target="_blank" >10.1063/1.4912774</a>

Result language
angličtina
Original language name
Maximizing vector distances using differential evolution - Relation to data redundancy
Original language description
This paper studies how redundant data affect maximizing of weighted distances of vectors in a set of vectors. To maximize distances differential evolution is used, because the problem does not have analytical solution and is complex. This paper at firstdescribes suppressing of redundant data mathematically and then it checks this theoretical result in two experiments practically. As a result it was found that both experiments are in correspondence with theory.
Czech name
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Czech description
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Project
<a href="/en/project/ED2.1.00%2F03.0089" target="_blank" >ED2.1.00/03.0089: The Centre of Security, Information and Advanced Technologies (CEBIA-Tech)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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