基于云模型的自适应量子免疫克隆算法

利用云模型能够兼顾随机性和模糊性的品质,提出一种基于云模型的自适应量子免疫克隆算法.使用云算子代替通用的量子旋转门这一量子进化算法核心算子用于寻优变异操作;通过控制云算子间的协作,实现算法在进化过程中对搜索范围的动态调整,使算法具有较强的全局搜索能力;同时,补充针对性的优化方案,有效避免了算法陷入局部最优.对标准数值优化问题的仿真对比实验表明,该算法具有寻优能力强、搜索精度高、稳定度好等优点;对非线性系统的参数估计仿真实验,该算法也取得了对参数的高精度有效估计.

Quantum Adaptive Immune Clone Algorithm Based on Cloud Model

Based on a cloud model,which makes good balance between randomness and fuzziness,a quantum adaptive immune clone algorithm is proposed.The quantum rotate gate,a key operator of quantum evolutionary algorithm for optimization and mutation operation,is insteaded by cloud operators.Dynamic adjustment of searching range in evolutionary process is realized by controlling collaboration of cloud operators.It makes the algorithm has strong ability in global search.Programs are modified for targeted optimization.They make algorithm avoid falling into local optimum effectively.Simulation experiments for standard numerical optimization problems show that the proposed algorithm has better search capability,higher search precision,and better stability.Simulation experiment in parameters estimation of nonlinear system shows that the algorithm gets effectively estimation for system parameters with high accuracy and good performance.