基于逻辑自映射的变尺度Henon搜索蜂群算法

Artificial Bee Colony Algorithm Based on Logic Self Mapping and Henon Search with Variable Scale

鉴于Henon映射的自组织特性,提出基于Henon映射变尺度搜索的蜂群优化算法,通过Henon映射的逻辑自组织映射能力,在蜂群寻优搜索到的引领蜂群扰动附近的自组织变尺度搜索更优特征解,同时对这搜索范围进行变尺度动态调整收缩。最后将蜂群仿生优化算法应用到强干扰瑞利分布色噪声下微弱信号检测仿真实验和应用中,仿真实验表明,改进的蜂群优化算法显著提高了优化性能,寻优检测精度更高,并能实现全局快速收敛,能有效对强干扰下的微弱信号进行有效检测,检测性能提高显著。

In view of the self-organization characteristics of Henon mapping, the bee colony optimization algorithm was pro-posed based on Henon mapping and its variable scale search. And the logic self organizing mapping ability was used, and the most feature solution was searched with variable scale for bee colony disturbance performance. The searching range was adjusted with dynamic adjustment contraction. Finally, it was applied in the weak signal detection in the strong disturbance with Rayleigh distribution of color noise. Simulation result shows that the improved algorithm can optimize the detection performance greatly, and the searching precision is improved perfectly with fast convergence, the detection performance is improved greatly, and it can be applied in the weak signal detection in practice.