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属性约简是粗糙集理论的核心部分.受细菌觅食过程的启发,本文将细菌觅食算法的思想应用于粒子群算法,提出了一种细菌觅食粒子群算法.细菌觅食过程的趋向操作可以指导粒子朝着更优方向进化,而粒子群算法又能提高细菌觅食算法的收敛速度和寻优能力.将该算法应用到属性约简中,数值实验结果表明,本文提出的细菌觅食粒子群优化的约简算法在寻优能力方面均优于Hu算法、粒子群约简算法和细菌觅食约简算法,能得到更好的最小属性约简.
Attribute reduction is the core part of rough set theory.Inspired by the process of bacterial foraging, this paper applies the idea of bacterial foraging algorithm to particle swarm optimization and proposes a bacterial foraging particle swarm optimization algorithm. The particle swarm optimization algorithm can improve the convergence speed and optimization ability of the bacteria foraging algorithm.This algorithm is applied to attribute reduction, numerical experiments show that the bacteria proposed in this paper seek The PSO reduction algorithm is better than the Hu algorithm, the particle swarm reduction algorithm and the bacterial foraging reduction algorithm in optimization ability, which can get a better minimum attribute reduction.