Dynamic trajectory and convergence analysis of swarm algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86092948" target="_blank" >RIV/61989100:27240/12:86092948 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Dynamic trajectory and convergence analysis of swarm algorithm
Original language description
Swarm Intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment cause coherent functional global patterns to emerge. Although the swarm algorithms have exhibited good performance across a wide range of application problems, it is difficult to analyze the convergence. In this paper, we discuss the dynamic trajectory and convergence of the swarm intelligent model, namely the particle swarmalgorithm. We explore the tradeoff between exploration and exploitation using differential analysis and Laplace transform. The trajectories are parsed into first-order inertial element and second-order oscillation element. Their transfer functions are derived, and the trajectories are described in explicit time functions. The first-order inertial element is helpful to maintain the trajectory's stability and algorithm convergence, while the second-order oscillation element trends to explo
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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