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基于时变Sigmoid函数的鲁棒PSO算法

, PP. 1650-1654

Keywords: 粒子群优化,鲁棒最优解,时变,Sigmoid,函数

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Abstract:

在样本规模有限的情况下,为了提高算法的鲁棒优化性能,提出一种基于时变(随迭代次数变化)Sigmoid函数的鲁棒粒子群优化算法.采用拟蒙特卡罗积分方法近似估计有效目标函数,以时变Sigmoid函数为基础,设计各代各样本规模的选取概率.迭代前期,样本规模期望值较小,加快了算法探索速度;迭代后期,样本规模期望值较大,提高了算法的开发精度.标准测试函数仿真结果显示,所提出方法具有较优的鲁棒优化性能.

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