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The Standard Particle Swarm Optimization Algorithm Convergence Analysis and Parameter Selection

机译:标准粒子群优化算法收敛分析和参数选择

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Formal sufficient and necessary condition for the deterministic standard PSO algorithm to converge to equilibrium point, diverge to infinity or oscillate within a range is derived based on the discrete time dynamic system theory. General guidelines for parameters selection are provided according to the theory analysis. It is pointed out that, strictly speaking, the currently popular view that small inertia weight will facilitate a local search is not accurate enough. And the condition for the view to hold is given. The simulation results of particle trajectories are given to illustrate and verify the theory analysis.
机译:确定性标准PSO算法将达到平衡点的正式充分和必要条件,基于离散时间动态系统理论导出到无限远的离散或振荡的偏离。根据理论分析提供参数选择的一般指南。有人指出,严格来说,目前流行的惯性重量将有助于本地搜索不够准确。给出了持有的视图的条件。给出了粒子轨迹的仿真结果说明并验证了理论分析。

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