Publikace UTB
Repozitář publikační činnosti UTB

SHADE algorithm dynamic analyzed through complex network

Repozitář DSpace/Manakin

Název: SHADE algorithm dynamic analyzed through complex network
Autor: Viktorin, Adam; Šenkeřík, Roman; Pluháček, Michal; Kadavý, Tomáš
Typ dokumentu: Článek ve sborníku (English)
Zdrojový dok.: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017, vol. 10392 LNCS, p. 666-677
ISSN: 0302-9743 (Sherpa/RoMEO, JCR)
Journal Impact This chart shows the development of journal-level impact metrics in time
JCR Journal Citation Reports - Impact Factor
SNIP SCImago Source Normalized Impact per Paper
SJR SCImago Journal Rank
IPP SCImago Impact per Publication
CS Scopus CiteScore
(Note: The metrics are not comparable against one another.)
ISBN: 978-3-319-62388-7
DOI: https://doi.org/10.1007/978-3-319-62389-4_55
Abstrakt: In this preliminary study, the dynamic of continuous optimization algorithm Success-History based Adaptive Differential Evolution (SHADE) is translated into a Complex Network (CN) and the basic network feature, node degree centrality, is analyzed in order to provide helpful insight into the inner workings of this state-of-the-art Differential Evolution (DE) variant. The analysis is aimed at the correlation between objective function value of an individual and its participation in production of better offspring for the future generation. In order to test the robustness of this method, it is evaluated on the CEC2015 benchmark in 10 and 30 dimensions.
Plný text: https://link.springer.com/chapter/10.1007/978-3-319-62389-4_55
Zobrazit celý záznam

Find Full text Export to RefWorks
   

 

Soubory tohoto záznamu

Icon
Název: Fulltext_1007477.pdf
Velikost: 1.109Mb
Formát: PDF
Popis: fulltext

Citace ČSN ISO 690:2011

Citace článku v konferenčním sborníku:
VIKTORIN, Adam, Roman ŠENKEŘÍK, Michal PLUHÁČEK a Tomáš KADAVÝ. SHADE algorithm dynamic analyzed through complex network. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [online]. Hong Kong: Springer Verlag, 2017, s. 666-677. [cit. 2024-11-16]. ISSN 0302-9743. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-319-62389-4_55.

Tyto citace vytvořil software a mohou obsahovat chyby. Pro ověření přesnosti si nastudujte příslušnou citační normu nebo příručku.

Související články