Deep swarm: Nested particle swarm optimization

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dc.contributor.authorEberhart, Russell C.
dc.contributor.authorGroves, Doyle J.
dc.contributor.authorWoodward, Joshua K.
dc.contributor.departmentElectrical and Computer Engineering, School of Engineering and Technologyen_US
dc.date.accessioned2019-02-28T15:48:29Z
dc.date.available2019-02-28T15:48:29Z
dc.date.issued2017-11
dc.description.abstractA new generation of particle swarm optimization (PSO) has been developed that automatically evolves optimal or near-optimal values for parameters of the PSO algorithm such as population size and neighborhood size, and, if used, parameters of associated neural network(s), such as number of hidden processing elements (PEs). Called Deep Swarm, it is a nested version of PSO, and comprises swarms within a swarm.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationEberhart, R. C., Groves, D. J., & Woodward, J. K. (2017). Deep swarm: Nested particle swarm optimization. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1–6). https://doi.org/10.1109/SSCI.2017.8280920en_US
dc.identifier.urihttps://hdl.handle.net/1805/18509
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/SSCI.2017.8280920en_US
dc.relation.journal2017 IEEE Symposium Series on Computational Intelligenceen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjectparticleen_US
dc.subjectswarmen_US
dc.subjectoptimizationen_US
dc.titleDeep swarm: Nested particle swarm optimizationen_US
dc.typeConference proceedingsen_US
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