Original scientific paper
https://doi.org/10.17559/TV-20151021202802
A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle
Zsolt Csaba Johanyák
orcid.org/0000-0001-9285-9178
; Department of Information Technology, Pallasz Athéné University, Izsáki út 10., H-6000, Kecskemét, Hungary
Full text: english pdf 1.042 Kb
page 295-301
downloads: 514
cite
APA 6th Edition
Johanyák, Z.C. (2017). A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle. Tehnički vjesnik, 24 (Supplement 2), 295-301. https://doi.org/10.17559/TV-20151021202802
MLA 8th Edition
Johanyák, Zsolt Csaba. "A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle." Tehnički vjesnik, vol. 24, no. Supplement 2, 2017, pp. 295-301. https://doi.org/10.17559/TV-20151021202802. Accessed 22 Nov. 2024.
Chicago 17th Edition
Johanyák, Zsolt Csaba. "A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle." Tehnički vjesnik 24, no. Supplement 2 (2017): 295-301. https://doi.org/10.17559/TV-20151021202802
Harvard
Johanyák, Z.C. (2017). 'A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle', Tehnički vjesnik, 24(Supplement 2), pp. 295-301. https://doi.org/10.17559/TV-20151021202802
Vancouver
Johanyák ZC. A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle. Tehnički vjesnik [Internet]. 2017 [cited 2024 November 22];24(Supplement 2):295-301. https://doi.org/10.17559/TV-20151021202802
IEEE
Z.C. Johanyák, "A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle", Tehnički vjesnik, vol.24, no. Supplement 2, pp. 295-301, 2017. [Online]. https://doi.org/10.17559/TV-20151021202802
Full text: croatian pdf 1.042 Kb
page 295-301
downloads: 1.041
cite
APA 6th Edition
Johanyák, Z.C. (2017). A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle. Tehnički vjesnik, 24 (Supplement 2), 295-301. https://doi.org/10.17559/TV-20151021202802
MLA 8th Edition
Johanyák, Zsolt Csaba. "A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle." Tehnički vjesnik, vol. 24, no. Supplement 2, 2017, pp. 295-301. https://doi.org/10.17559/TV-20151021202802. Accessed 22 Nov. 2024.
Chicago 17th Edition
Johanyák, Zsolt Csaba. "A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle." Tehnički vjesnik 24, no. Supplement 2 (2017): 295-301. https://doi.org/10.17559/TV-20151021202802
Harvard
Johanyák, Z.C. (2017). 'A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle', Tehnički vjesnik, 24(Supplement 2), pp. 295-301. https://doi.org/10.17559/TV-20151021202802
Vancouver
Johanyák ZC. A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle. Tehnički vjesnik [Internet]. 2017 [cited 2024 November 22];24(Supplement 2):295-301. https://doi.org/10.17559/TV-20151021202802
IEEE
Z.C. Johanyák, "A modified particle swarm optimization algorithm for the optimization of a fuzzy classification subsystem in a series hybrid electric vehicle", Tehnički vjesnik, vol.24, no. Supplement 2, pp. 295-301, 2017. [Online]. https://doi.org/10.17559/TV-20151021202802
Abstract
Particle swarm optimization (PSO) based optimization algorithms are simple and easily implementable techniques with low computational complexity, which makes them good tools for solving large-scale nonlinear optimization problems. This paper presents a modified version of the original method by combining PSO with a local search technique at the end of each iteration cycle. The new algorithm is applied for the task of parameter optimization of a fuzzy classification subsystem in a series hybrid electric vehicle (SHEV) aiming at the reduction of the harmful pollutant emission. The new method ensured a better fitness value than either the original PSO algorithm or the clonal selection based artificial immune system algorithm (CLONALG) by using similar parameters.
Keywords
classification; fuzzy logic; hybrid electric vehicle; particle swarm optimization
Hrčak ID:
186068
URI
https://hrcak.srce.hr/186068
Publication date:
2.9.2017.
Article data in other languages:
croatian
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