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- W2388871457 abstract "In application of particle swarm optimization algorithm,the solution is usually misled to local minima resulting in compromised searching efficiency.To cope this drawback,the division of subpopulation and self-adaptive inertia weight are incorporated to PSO.The particle swarm is divided by subpopulation into subgroups close to the center of the swarm with the best fitness value judged by the similarity of particle swarm.Test of the improved algorithm using six benchmark functions indicates that the algorithm is capable of locating the global optimal value with less time-consumption and higher efficiency." @default.
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- W2388871457 date "2008-01-01" @default.
- W2388871457 modified "2023-09-22" @default.
- W2388871457 title "Study on an Improved Particle Swarm Optimization Algorithm for Solving Multi-peak Function" @default.
- W2388871457 hasPublicationYear "2008" @default.
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