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Orthogonal learning firefly algorithm

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Název: Orthogonal learning firefly algorithm
Autor: Kadavý, Tomáš; Pluháček, Michal; Viktorin, Adam; Šenkeřík, Roman
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 Artificial Intelligent Systems (HAIS 2018). 2018, vol. 10870 LNAI, p. 315-326
ISSN: 0302-9743 (Sherpa/RoMEO, JCR)
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ISBN: 978-3-319-92638-4
DOI: https://doi.org/10.1007/978-3-319-92639-1_26
Abstrakt: In this paper, a proven technique, orthogonal learning, is combined with popular swarm metaheuristic Firefly Algorithm (FA). More precisely with its hybrid modification Firefly Particle Swarm Optimization (FFPSO). The performance of the developed algorithm is tested and compared with canonical FA and above mentioned FFPSO. Comparisons have been conducted on well-known CEC 2017 benchmark functions, and the results have been evaluated for statistical significance using Friedman rank test. © Springer International Publishing AG, part of Springer Nature 2018.
Plný text: https://link.springer.com/chapter/10.1007/978-3-319-92639-1_26
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Citace článku v konferenčním sborníku:
KADAVÝ, Tomáš, Michal PLUHÁČEK, Adam VIKTORIN a Roman ŠENKEŘÍK. Orthogonal learning firefly algorithm. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [online]. Oviedo: Springer Verlag, 2018, s. 315-326. [cit. 2024-11-09]. ISSN 0302-9743. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-319-92639-1_26.

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