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A New PSO Model Mimicking Bio-parasitic Behavior

机译:一种模拟生物寄​​生行为的新PSO模型

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Based on the analysis of biological symbiotic relationship, the mechanism of facultative parasitic behaviour is embedded into the particle swarm optimization (PSO) to construct a two-population PSO model called PSOPB, composed of the host and the parasites population. In this model, the two populations exchange particles according to the fitness sorted in a certain number of iterations. In order to embody the law of "survival of the fittest" in biological evolution, the poor fitness particles in the host population are eliminated, replaced by the re-initialization of the particles in order to maintain constant population size. The results of experiments of a set of 6 benchmark functions show that presented algorithm model has faster convergence rate and higher search accuracy compared with CPSO, PSOPC and PSO-LIW.
机译:在分析生物共生关系的基础上,将兼性寄生行为的机制嵌入粒子群优化(PSO)中,以构建由宿主和寄生虫种群组成的两种群PSO模型,称为PSOPB。在此模型中,两个种群根据在一定数量的迭代中排序的适应性交换粒子。为了在生物进化中体现“适者生存”的规律,消除宿主种群中适应性差的颗粒,取而代之的是重新初始化颗粒以保持种群恒定。一组6个基准函数的实验结果表明,与CPSO,PSOPC和PSO-LIW相比,所提出的算法模型具有更快的收敛速度和更高的搜索精度。

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