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- W2110402926 abstract "This paper proposes a novel optimization algorithm - adaptive chaotic particle swarm optimization (ACPSO). The short-term chaotic search is applied to the best particle in the iteration and an adaptive mechanism is used to control the scale of chaotic turbulence, which can avoid trapping in local optima and improve the searching performance of chaotic particle swarm optimization (CPSO). Simulation results and comparisons with the standard particle swarm optimization (PSO) illustrate the effectiveness of the ACPSO and show that the ACPOS has super ability in balancing the exploration and exploitation." @default.
- W2110402926 created "2016-06-24" @default.
- W2110402926 creator A5060100779 @default.
- W2110402926 date "2009-08-01" @default.
- W2110402926 modified "2023-10-01" @default.
- W2110402926 title "An adaptive chaotic particle swarm optimization" @default.
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- W2110402926 doi "https://doi.org/10.1109/cccm.2009.5270407" @default.
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