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中文摘要：
基于云模型在定性与定量之间相互转换的优良特性，结合粒子群算法的基本思想，提出一种云变异粒子群优化算法．其核心思想是通过正态云算子实现粒子的进化学习过程和变异操作．利用云模型对粒子的进化和变异进行统一建模，自适应控制粒子的搜索范围．典型复杂函数测试表明，云粒子群算法能有效找出全局最优解，特别适宜于多峰值函数寻优．
英文摘要：
Integrated with the basic principle of particle swarm optimization, a rapid evolutionary algorithm is proposed based on the characteristics of the cloud model on the process of transforming a qualitative concept to a set of quantitative numerical values, namely cloud hypermutation particle swarm optimization algorithm. Its core idea is to achieve the evolution of the learning process and the mutation operation by the normal cloud particle operator. With the cloud model, inheritance and mutation of the particle can be modeled naturally and uniformly, which makes it easy and nature to control the scale of the searching space. The simulation results show that the proposed algorithm has fine capability of finding global optimum, especially for multimodal function.
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