This HTML5 document contains 43 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dctermshttp://purl.org/dc/terms/
n5http://localhost/temp/predkladatel/
n15http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n13http://linked.opendata.cz/resource/domain/vavai/projekt/
n18http://linked.opendata.cz/resource/domain/vavai/subjekt/
n7http://linked.opendata.cz/ontology/domain/vavai/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
n8http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F61988987%3A17610%2F13%3AA13015RP%21RIV13-MSM-17610___/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n16http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n17http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n19http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n14http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n12http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n10http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n9http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F61988987%3A17610%2F13%3AA13015RP%21RIV13-MSM-17610___
rdf:type
n7:Vysledek skos:Concept
dcterms:description
The paper deals with the adaptive mechanisms in differential evolution (DE) algorithm. DE is a simple and effective stochastic algorithm frequently used in solving the real-world global optimization problems. The efficiency of the algorithm is sensitive to setting its control parameters. Several adaptive approaches have appeared recently in order to avoid control-parameter tuning. A new adaptive variant of differential evolution is proposed in this study. It is based on a combination of two adaptive approaches published before. The new algorithm was tested on the well-known set of benchmark problems developed for the special session of CEC2005 at four levels of population size and its performance was compared with the adaptive variants that were applied in the design of the new algorithm. The new adaptive DE variant outperformed the others in several test problems but its efficiency on average was not better. The paper deals with the adaptive mechanisms in differential evolution (DE) algorithm. DE is a simple and effective stochastic algorithm frequently used in solving the real-world global optimization problems. The efficiency of the algorithm is sensitive to setting its control parameters. Several adaptive approaches have appeared recently in order to avoid control-parameter tuning. A new adaptive variant of differential evolution is proposed in this study. It is based on a combination of two adaptive approaches published before. The new algorithm was tested on the well-known set of benchmark problems developed for the special session of CEC2005 at four levels of population size and its performance was compared with the adaptive variants that were applied in the design of the new algorithm. The new adaptive DE variant outperformed the others in several test problems but its efficiency on average was not better.
dcterms:title
A Combined Approach to Adaptive Differential Evolution A Combined Approach to Adaptive Differential Evolution
skos:prefLabel
A Combined Approach to Adaptive Differential Evolution A Combined Approach to Adaptive Differential Evolution
skos:notation
RIV/61988987:17610/13:A13015RP!RIV13-MSM-17610___
n7:predkladatel
n18:orjk%3A17610
n3:aktivita
n14:S n14:P
n3:aktivity
P(ED1.1.00/02.0070), S
n3:cisloPeriodika
1
n3:dodaniDat
n9:2013
n3:domaciTvurceVysledku
n15:3951855 n15:3210340
n3:druhVysledku
n12:J
n3:duvernostUdaju
n17:S
n3:entitaPredkladatele
n8:predkladatel
n3:idSjednocenehoVysledku
58474
n3:idVysledku
RIV/61988987:17610/13:A13015RP
n3:jazykVysledku
n19:eng
n3:klicovaSlova
global optimization; differential evolution; adaption; combined adaptive mechanism; experimental comparison
n3:klicoveSlovo
n16:combined%20adaptive%20mechanism n16:experimental%20comparison n16:global%20optimization n16:differential%20evolution n16:adaption
n3:kodStatuVydavatele
CZ - Česká republika
n3:kontrolniKodProRIV
[9AD878631C0C]
n3:nazevZdroje
NEURAL NETW WORLD
n3:obor
n10:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n13:ED1.1.00%2F02.0070
n3:rokUplatneniVysledku
n9:2013
n3:svazekPeriodika
23
n3:tvurceVysledku
Tvrdík, Josef Poláková, Radka
s:issn
1210-0552
s:numberOfPages
13
n5:organizacniJednotka
17610