improving_the_performance_of_pso_using_adaptive_de
所属分类:数值算法/人工智能
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上传日期:2008-01-27 23:47:35
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skylizm
说明: Swarm intelligence algorithms are based on natural
behaviors. Particle swarm optimization (PSO) is a
stochastic search and optimization tool. Changes in the
PSO parameters, namely the inertia weight and the
cognitive and social acceleration constants, affect the
performance of the search process. This paper presents a
novel method to dynamically change the values of these
parameters during the search. Adaptive critic design
(ACD) has been applied for dynamically changing the
values of the PSO parameters.
(Swarm intelligence algorithms are based on naturalbehaviors. Particle swarm optimization (PSO) is astochastic search and optimization tool. Changes in thePSO parameters, namely the inertia weight and thecognitive and social acceleration constants, affect theperformance of the search process. This paper presents anovel method to dynamically change the values of theseparameters during the search. Adaptive critic design (ACD) has been applied for dynamically changing thevalues of the PSO parameters.)
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improving_the_performance_of_pso_using_adaptive_designs.pdf (381894, 2006-07-11)
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