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DC Field | Value | Language |
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dc.contributor.author | Fang, J | - |
dc.contributor.author | Liu, W | - |
dc.contributor.author | Chen, L | - |
dc.contributor.author | Lauria, S | - |
dc.contributor.author | Miron, A | - |
dc.contributor.author | Liu, X | - |
dc.date.accessioned | 2024-04-22T14:09:02Z | - |
dc.date.available | 2024-04-22T14:09:02Z | - |
dc.date.issued | 2023-03-27 | - |
dc.identifier | ORCD: Weibo Liu https://orcid.org/0000-0002-8169-3261 | - |
dc.identifier | ORCiD: Stanislao Lauria https://orcid.org/0000-0003-1954-1547 | - |
dc.identifier | ORCiD: Alina Miron https://orcid.org/0000-0002-0068-4495 | - |
dc.identifier | ORCiD: Xiaohui Liu https://orcid.org/0000-0003-1589-1267 | - |
dc.identifier.citation | Fang, J. et al. (2023) 'A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization', International Journal of Network Dynamics and Intelligence, 2 (1), pp. 24 - 50. doi: 10.53941/ijndi0201002. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/28842 | - |
dc.description.abstract | Particle swarm optimization (PSO) is a popular heuristic method, which is capable of effectively dealing with various optimization problems. A detailed overview of the original PSO and some PSO variant algorithms is presented in this paper. An up-to-date review is provided on the development of PSO variants, which include four types i.e., the adjustment of control parameters, the newly-designed updating strategies, the topological structures, and the hybridization with other optimization algorithms. A general overview of some selected applications (e.g., robotics, energy systems, power systems, and data analytics) of the PSO algorithms is also given. In this paper, some possible future research topics of the PSO algorithms are also introduced. | en_US |
dc.description.sponsorship | This research received no external funding. | en_US |
dc.format.extent | 24 - 50 | - |
dc.format.medium | Electronic | - |
dc.language | English | - |
dc.language.iso | en | en_US |
dc.publisher | Scilight Press | en_US |
dc.rights | Copyright: © 2023 by the authors. This is an open access article under the terms and conditions of the Creative Commons Attribution (CC BY) license https://creativecommons.org/licenses/by/4.0/. | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | particle swarm optimization | en_US |
dc.subject | optimization | en_US |
dc.subject | evolutionary computation | en_US |
dc.subject | inertia weight | en_US |
dc.subject | acceleration coefficient | en_US |
dc.title | A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization | en_US |
dc.type | Article | en_US |
dc.date.dateAccepted | 2022-11-28 | - |
dc.identifier.doi | https://doi.org/10.53941/ijndi0201002 | - |
dc.relation.isPartOf | International Journal of Network Dynamics and Intelligence | - |
pubs.issue | 1 | - |
pubs.publication-status | Published online | - |
pubs.volume | 2 | - |
dc.identifier.eissn | 2653-6226 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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