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Multi-chaotic approach for particle acceleration in PSO

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Název: Multi-chaotic approach for particle acceleration in PSO
Autor: Pluháček, Michal; Šenkeřík, Roman; Viktorin, Adam; 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)Hybrid Metaheuristics (HM 2016). 2016, vol. 9668, p. 75-86
ISSN: 0302-9743 (Sherpa/RoMEO, JCR)
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ISBN: 978-3-319-39635-4
DOI: https://doi.org/10.1007/978-3-319-39636-1_6
Abstrakt: This paper deals with novel approach for hybridization of two scientific techniques: the evolutionary computational techniques and deterministic chaos. The Particle Swarm Optimization algorithm is enhanced with two pseudo-random number generators based on chaotic systems. The chaotic pseudo-random number generators (CPRNGs) are used to guide the particles movement through multiplying the accelerating constants. Different CPRNGs are used simultaneously in order to improve the performance of the algorithm. The IEEE CEC’13 benchmark suite is used to test the performance of the proposed method. © Springer International Publishing Switzerland 2016.
Plný text: https://link.springer.com/chapter/10.1007/978-3-319-39636-1_6
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Citace článku v konferenčním sborníku:
PLUHÁČEK, Michal, Roman ŠENKEŘÍK, Adam VIKTORIN a Ivan ZELINKA. Multi-chaotic approach for particle acceleration in PSO. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [online]. Plymouth: Springer Verlag, 2016, s. 75-86. [cit. 2024-11-25]. ISSN 0302-9743. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-319-39636-1_6.

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