dc.contributor.author |
Van den Bergh, F
|
|
dc.contributor.author |
Engelbrecht, AP
|
|
dc.date.accessioned |
2007-08-23T11:51:40Z |
|
dc.date.available |
2007-08-23T11:51:40Z |
|
dc.date.issued |
2006 |
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dc.identifier.citation |
Van den Bergh, F and Engelbrecht, AP. 2006. Study of particle swarm optimization particle trajectories. Information Sciences, Vol. 176, pp 937–971 |
en |
dc.identifier.issn |
0020-0255 |
|
dc.identifier.uri |
http://hdl.handle.net/10204/1155
|
|
dc.description |
Copyright: 2005 Elsevier Science B.V |
en |
dc.description.abstract |
Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Most of the PSO studies are empirical, with only a few theoretical analyses that concentrate on understanding particle trajectories. These theoretical studies concentrate mainly on simplified PSO systems. This paper overviews current theoretical studies, and extend these studies to investigate particle trajectories for general swarms to include the influence of the inertia term. The paper also provides a formal proof that each particle converges to a stable point. An empirical analysis of multidimensional stochastic particles is also presented. Experimental results are provided to support the conclusions drawn from the theoretical findings |
en |
dc.language.iso |
en |
en |
dc.publisher |
Elsevier Science B.V |
en |
dc.subject |
Particle swarm optimization |
en |
dc.subject |
Particle trajectories |
en |
dc.subject |
Equilibrium |
en |
dc.subject |
Convergence |
en |
dc.title |
Study of particle swarm optimization particle trajectories |
en |
dc.type |
Article |
en |
dc.identifier.apacitation |
Van den Bergh, F., & Engelbrecht, A. (2006). Study of particle swarm optimization particle trajectories. http://hdl.handle.net/10204/1155 |
en_ZA |
dc.identifier.chicagocitation |
Van den Bergh, F, and AP Engelbrecht "Study of particle swarm optimization particle trajectories." (2006) http://hdl.handle.net/10204/1155 |
en_ZA |
dc.identifier.vancouvercitation |
Van den Bergh F, Engelbrecht A. Study of particle swarm optimization particle trajectories. 2006; http://hdl.handle.net/10204/1155. |
en_ZA |
dc.identifier.ris |
TY - Article
AU - Van den Bergh, F
AU - Engelbrecht, AP
AB - Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Most of the PSO studies are empirical, with only a few theoretical analyses that concentrate on understanding particle trajectories. These theoretical studies concentrate mainly on simplified PSO systems. This paper overviews current theoretical studies, and extend these studies to investigate particle trajectories for general swarms to include the influence of the inertia term. The paper also provides a formal proof that each particle converges to a stable point. An empirical analysis of multidimensional stochastic particles is also presented. Experimental results are provided to support the conclusions drawn from the theoretical findings
DA - 2006
DB - ResearchSpace
DP - CSIR
KW - Particle swarm optimization
KW - Particle trajectories
KW - Equilibrium
KW - Convergence
LK - https://researchspace.csir.co.za
PY - 2006
SM - 0020-0255
T1 - Study of particle swarm optimization particle trajectories
TI - Study of particle swarm optimization particle trajectories
UR - http://hdl.handle.net/10204/1155
ER -
|
en_ZA |