Study and Improvement on Particle Swarm Algorithm

Hui Xu1; Yongguo Yang2; Lei Mao1

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Study and Improvement on Particle Swarm Algorithm

机译：粒子群算法的研究与改进

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—An improved particle swarm optimizer (IPSO) with artificial immune algorithm (AIA) is proposed based on basic particle swarm optimization (BPSO). IPSO which is divided into two phases during the evolutionary process is different from BPSO. AIA remaining the diversity of population is applied in the first phase. Sub-population is formed by the optimum values sorted near the top from the first phase. Some sub-population evaluate at the same time to improve the performance of local convergence and get the global optimum value. Most Benchmark function get good result with IPSO which ability of optimization is better than BPSO.

机译：- 基于基础粒子群优化（BPSO），提出了具有人工免疫算法（AIA）的改进的粒子群优化器（IPSO）。在进化过程中分为两个阶段的IPSO与BPSO不同。 AIA剩下的人口多样性适用于第一阶段。通过从第一阶段附近的最佳值形成亚群。一些子人口同时评估局部收敛性的性能并获得全局最佳值。大多数基准函数都能通过IPSO获得好结果，优化能力优于BPSO。

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《Journal of Computers》 |2013年第4期|共6页
作者
Hui Xu1; Yongguo Yang2; Lei Mao1;
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Study and Improvement on Particle Swarm Algorithm

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