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《Journal of Anqing Teachers College(Natural Science Edition)》 2008-02
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Adaptive Particle Swarm Optimization Algorithm with Dynamically Changing Inertia Weight

ZHANG Xiao-ping1,GAO Yue-lin2 (1 School of Mathematics and Computer,Ningxia University,Yinchuan 750021,2 Research Institute of Information and System Computation Science,North National University,Yinchuan 750021,China)  
A new adaptive particle swarm Optimization algorithm with dynamically changing inertia weight(APSO) is presented to solve the problem that the linearly decreasing weight(LDW) of the particle swarm algorithm cannot find out the optimum values sufficiently with high inertia weight.The algorithm also cannot adapt to the complex and nonlinear optimization process.During the running time,the inertia weight is determined by the particle's fitness that makes the algorithm become dynamical and adaptive.The experimental results show that the new algorithm not only has great advantage of convergence speed and accuracy,but also can increase the convergence accuracy.
【Fund】: 国家社会科学基金项目资助(07XJY038);; 国家教育部社科规划项目资助(06JA630056)
【CateGory Index】: TP301.6
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