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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F07%3A03132428%21RIV08-MSM-21230___
rdf:type
n3:Vysledek skos:Concept
dcterms:description
This paper introduces a novel stochastic and population based binary optimization method inspired by social psychology. It is called Social Impact Theory based Optimization (SITO). The method has been developed with the use of some simple modications of simulations of Latane's Dynamic Social Impact Theory. The usability of the algorithm is demonstrated via experimental testing on some test problems. The results showed that the initial version of SITO performs comparably to the simple Genetic Algorithm (GA) and the binary Particle Swarm Optimization (bPSO). Článek popisuje novou stochastickou a na populaci založenou metaheuristiku inspirovanou sociální psychologií. Metoda je nazvána Social Impact Theory based Optimizer. Metoda byla vyvinuta s použitím modifikace Lataného dynamické teorie sociálního vlivu. Funkčnost metody je demonstrována experimenty s použitím jednoduchých testovacích funkcí. Výsledky ukazují srovnatelnou výkonost nového algoritmu v porovnání s genetickými algoritmy a binární PSO metodou. This paper introduces a novel stochastic and population based binary optimization method inspired by social psychology. It is called Social Impact Theory based Optimization (SITO). The method has been developed with the use of some simple modications of simulations of Latane's Dynamic Social Impact Theory. The usability of the algorithm is demonstrated via experimental testing on some test problems. The results showed that the initial version of SITO performs comparably to the simple Genetic Algorithm (GA) and the binary Particle Swarm Optimization (bPSO).
dcterms:title
Optimalizátor založený na teorii sociálního vlivu Social Impact Theory based Optimizer Social Impact Theory based Optimizer
skos:prefLabel
Social Impact Theory based Optimizer Social Impact Theory based Optimizer Optimalizátor založený na teorii sociálního vlivu
skos:notation
RIV/68407700:21230/07:03132428!RIV08-MSM-21230___
n5:strany
635;644
n5:aktivita
n8:Z
n5:aktivity
Z(MSM6840770012)
n5:dodaniDat
n14:2008
n5:domaciTvurceVysledku
n13:6579191 n13:9431446
n5:druhVysledku
n16:D
n5:duvernostUdaju
n6:S
n5:entitaPredkladatele
n19:predkladatel
n5:idSjednocenehoVysledku
450650
n5:idVysledku
RIV/68407700:21230/07:03132428
n5:jazykVysledku
n15:eng
n5:klicovaSlova
binary; metaheuristics; optimization; social impact; social psychology
n5:klicoveSlovo
n10:optimization n10:social%20psychology n10:binary n10:social%20impact n10:metaheuristics
n5:kontrolniKodProRIV
[1DC35652124F]
n5:mistoKonaniAkce
Lisbon
n5:mistoVydani
Heidelberg
n5:nazevZdroje
Advances in Artificial Life
n5:obor
n20:JD
n5:pocetDomacichTvurcuVysledku
2
n5:pocetTvurcuVysledku
2
n5:rokUplatneniVysledku
n14:2007
n5:tvurceVysledku
Lhotská, Lenka Macaš, Martin
n5:typAkce
n21:WRD
n5:zahajeniAkce
2007-09-10+02:00
n5:zamer
n9:MSM6840770012
s:numberOfPages
10
n12:hasPublisher
Springer-Verlag
n4:isbn
978-3-540-74912-7
n17:organizacniJednotka
21230