CAJ | 학술논문

文章在分析基本人工鱼群算法(AFSA)的基础上,提出了一种基于自适应能力的改进人工鱼群算法,在不明显增加算法计算复杂性的前提下,引入自适应移动和visual、step参数自适应调整策略,这对于克服算法优化后期收敛速度慢,感知和移动距离随机性大、寻优精度低等缺点具有显著效果.仿真测试表明,改进后的人工鱼群算法在很大程度上摆脱了局部极值吸引的能力,寻优精度明显提高.
문장재분석기본인공어군산법(AFSA)적기출상,제출료일충기우자괄응능력적개진인공어군산법,재불명현증가산법계산복잡성적전제하,인입자괄응이동화visual、step삼수자괄응조정책략,저대우극복산법우화후기수렴속도만,감지화이동거리수궤성대、심우정도저등결점구유현저효과.방진측시표명,개진후적인공어군산법재흔대정도상파탈료국부겁치흡인적능력,심우정도명현제고.
The paper puts forward an improved AFSA algorithm based on self-adapt ability after analyzing the original artificial fish-swarm algorithm, which not only draws into the self-adapt movement but also the self-adapt adjustment of visual and step with no extra calculate complexity, this will be helpful to overcome the slow convergence in the afterlife of its lifecycle, random perception and movement as well as the low precision of searching. The results of simulation show that the improved AFSA al-gorithm gets rid of the attraction ability of local peak, the precision of searching is improved obviously.