A new deterministic PSO algorithm for real-time systems implemented on low-power devices

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dc.authoridTalaska, Tomasz/0000-0001-7252-8013
dc.contributor.authorDlugosz, Zofia
dc.contributor.authorRajewski, Michal
dc.contributor.authorDlugosz, Rafal
dc.contributor.authorTalaska, Tomasz
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2024-05-19T14:46:10Z
dc.date.available2024-05-19T14:46:10Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThe paper presents a novel, deterministic particle swarm optimization (PSO) algorithm, facilitating its implementation in low-power application specific integrated circuits (ASIC) realized in CMOS technology. The PSO algorithms are commonly used in a variety of optimization problems. They allow to search for a global extreme in a selected fitness function, which is used for numerical modeling of specific optimized problems. The conventional version of the algorithm is relatively difficult to implement directly in hardware, especially when each particle is represented by a separate circuit working in parallel with other particles. In such a situation, each particle has to be equipped with its own copy of each function. One of the problems is, for example, an efficient realization of the random function block that provides for each particle some factors used in computing a cognitive and a social velocity components. In this paper we shows a novel way to work around this problem. In the proposed approach the random function does not need to be used. It has been replaced by a simple computationally deterministic mechanism, which at the level of the overall swarm allows for effective emulation of the former random mechanism. We proposed such simplifications that reduce the formulas describing the algorithm to only basic arithmetic and logic operations. Comprehensive investigations have shown that performance of the proposed approach is comparable with its original version or in may situations even better. The proposed algorithm was tested with numerous test functions (50 runs for each tested function), to verify its flexibility and adaptation abilities to different problems.(c) 2023 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.cam.2023.115225
dc.identifier.issn0377-0427
dc.identifier.issn1879-1778
dc.identifier.scopus2-s2.0-85151646154en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org10.1016/j.cam.2023.115225
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5459
dc.identifier.volume429en_US
dc.identifier.wosWOS:000976622400001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal of Computational and Applied Mathematicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectParticle Swarm Optimization Algorithmen_US
dc.subjectParallel Computingen_US
dc.subjectDeterministic Approachen_US
dc.subjectHardware Implementationen_US
dc.subjectLow Power Circuitsen_US
dc.subjectCmos Technologyen_US
dc.titleA new deterministic PSO algorithm for real-time systems implemented on low-power devicesen_US
dc.typeArticleen_US

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