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《Journal of System Simulation》 2006-10
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Adaptive Particle Swarm Optimization Algorithm and Simulation

HAN Jiang-hong, LI Zheng-rong, WEI Zhen-chun (School of Computer and Information, Hefei University of Technology, Hefei 230009, China)  
The reasons of premature convergence of Particle Swarm Optimization (PSO) Algorithm were analyzed. An adaptive PSO (APSO) was proposed, in which the inertia weight of the particle was adjusted adaptively based on the premature convergence degree of the swarm and the fitness of the particle. The diversity of inertia weight makes a compromise between the global convergence and convergence speed. Simulation results show that APSO not only effectively alleviates the problem of premature convergence, but also has fast convergence speed.
【Fund】: 国家自然科学基金(60404009);; 教育部博士点基金(20050359004).
【CateGory Index】: TP18;TP391.9
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