Kontaktujte nás | Jazyk: čeština English
Název: | Population diversity analysis in adaptive differential evolution variants with unconventional randomization schemes | ||||||||||
Autor: | Šenkeřík, Roman; Viktorin, Adam; Kadavý, Tomáš; Pluháček, Michal; Kazíková, Anežka; Diep, Quoc Bao; Zelinka, Ivan | ||||||||||
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)Artificial Intelligence And Soft Computing, ICAISC 2019, Pt II. 2019, vol. 11508 LNAI, p. 506-518 | ||||||||||
ISSN: | 0302-9743 (Sherpa/RoMEO, JCR) | ||||||||||
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ISBN: | 978-3-03-020911-7 | ||||||||||
DOI: | https://doi.org/10.1007/978-3-030-20912-4_46 | ||||||||||
Abstrakt: | This research represents a detailed insight into the modern and popular hybridization of unconventional quasiperiodic/chaotic sequences and evolutionary computation. It is aimed at the influence of different randomization schemes on the population diversity, thus on the performance, of two selected adaptive Differential Evolution (DE) variants. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo-random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the unconventional chaotic pseudo-random number generators. The population diversity is recorded for 15 test functions from the CEC 2015 benchmark set in 10D. © 2019, Springer Nature Switzerland AG. | ||||||||||
Plný text: | https://link.springer.com/chapter/10.1007/978-3-030-20912-4_46 | ||||||||||
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