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- W2121931134 abstract "To combat the problem of premature convergence observed in many applications of PSO, a novel self-adaptive particle swarm optimization algorithm-SAPSO is proposed in this paper. There exist two states for each particle in the SAPSO algorithm and a metric to measure a particlepsilas activity is defined which is used to choose which state it would reside. In order to balance a particlepsilas exploration and exploitation capability for different evolving phase, a self-adjusted inertia weight which varies dynamically with each particlepsilas evolution degree and the current swarm evolution degree is introduced into SAPSO algorithm. Simulation and comparisons based on several well-studied non-noisy problems and noisy problems demonstrate the effectiveness, efficiency and robustness of the proposed algorithm." @default.
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- W2121931134 date "2008-01-01" @default.
- W2121931134 modified "2023-09-27" @default.
- W2121931134 title "A Self-Adaptive Particle Swarm Optimization Algorithm" @default.
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- W2121931134 doi "https://doi.org/10.1109/csse.2008.142" @default.
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