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- W2373587674 abstract "In order to overcome the problems of poor local search and premature convergence on Particle Swarm Optimization(PSO) algorithm,an improved particle swarm optimization approach based on Dynamic Random Search Technique(DRST) and good-point set was proposed in this paper.DRST was introduced to optimize the current best position of the swarm.On the other hand,reinitialization with a good-point set manner was employed for the swarm falling into premature convergence to go out of the local optimum.Linear search in the negative gradient direction was also applied to accelerate the optimization.In the end,an experiment was given and the results show that the improved algorithm has rapid convergence,great ability of preventing premature convergence and better performance than Standard Particle Swarm Optimization(SPSO) and Dissipative Particle Swarm Optimization(DPSO)." @default.
- W2373587674 created "2016-06-24" @default.
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- W2373587674 date "2011-01-01" @default.
- W2373587674 modified "2023-09-28" @default.
- W2373587674 title "Improved particle swarm optimization based on dynamic random search technique and good-point set" @default.
- W2373587674 hasPublicationYear "2011" @default.
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