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中文摘要：
通过分析粒子群算法早熟现象的机理,研究早熟收敛的本质,并提出一种克服粒子群算法早熟现象的局部＂飞跃＂策略.应用仿真及系统工程实例表明,该方法能有效地改善粒子群算法在非线性全局优化上的早熟问题,提高了粒子群算法的全局搜索能力.
英文摘要：
By analyzing mechanism of premature phenomenon in particle swarm optimization（ PSO）,we found nature of premature convergence and proposed a ＂leap＂strategy to jump out of local minimum,making halted particles ＂renewed＂when they are trapped into a local optimum. The strategy is applied to nonlinear programming and results are encouraging. The improved PSO solves efficiently premature convergence of the algorithm applying in nonlinear optimizations and improves global search ability of PSO.
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