基于免疫量子粒子群优化的属性约简

受生物免疫系统启发,把疫苗提取和疫苗接种思想应用到量子粒子群算法,提出了免疫量子粒子群算法。免疫接种可以指导粒子朝着更优方向进化,提高了量子粒子群的收敛速度和寻优能力。分别采用Hu算法、粒子群算法、量子粒子群、免疫量子粒子群多种算法应用于粗糙集属性约简。实验结果表明,基于免疫量子粒子群优化的约简算法在收敛速度和寻优能力都取得了更好的效果。

Attribute Reduction Based on Quantum-Behaved Particle Swarm Optimization with Immunity

Enlightened by biological immune system, this paper applies the idea of vaccine extraction and vaccination, this paper proposes quantum-behaved particle swarm optimization with immunity algorithm (IQPSO). In this algorithm, vaccination can guide the particles to evolve towards much better direction. Experiments show that attribute reduction based on IQPSO algorithm achieve much better result both in convergence speed and optimization capabilities in comparison with other algorithms, such as Hu algorithm, particle swarm optimization, and quantum-behaved particle swarm optimization.