【摘要】 提出一种基于混沌思想的粒子群优化(CPSO)算法,它利用粒子群优化算法收敛速度快和混沌运动遍历性、随机性等特点,对原粒子群优化算法进行了改进.在算法的初始化阶段,对粒子的位置混沌初始化;在算法运行过程中,根据群体适应度方差来自适应地对粒子的位置进行混沌更新.对几种典型函数的测试结果表明:CPSO算法提高了对多维空间全局搜索能力,并有效避免早熟收敛现象.应用在作为高频段电容标准的四端对电容器计量中,仿真结果与实测值基本一致,也证明了该算法的有效性和实用性.更多还原

【Abstract】 Based on the chaos particle swarm optimization(CPSO),an algorithm was presented through the improvement of particle swarm optimization algorithm.At the beginning,the location of the particle was evaluated by chaos.During the running time,according to the variance of the population′s fitness,the chaotic location update of the particle was performed adaptively.The experimental results using the testing functions showed that the new algorithm is able to search the global optimizer and avoiding the premature convergence on the multidimensional variable space.When four-terminal-pair capacitor was used as capacitance standard in high-frequency range,the new algorithm showed its effectiveness and applicability.更多还原