Based on chaotic sequence of multimodal function particle swarm optimization algorithm goal is to find a multimodal function of all local optimization peak. On the analysis of particle swarm optimization Algorithm of various parameters on the particle motion influence on the basis of the particle swarm algorithm transform, let particle motion from the initial position along the optimization function curve to optimization peak Crawling direction. To find the area of the local optimization peak If you want to get as many local optimization peak, requires the particle swarm the particles in the initial position points Cloth has the nature of randomness and ergodicity. Therefore the chaotic sequence set particle initial position In order to make every local optimal value point may have particle swarm particles after, The variable step long iterative calculation To prevent optimization function curve of some local peak no nearby particle distribution, thus miss this local peak, the c

基于混沌序列的多峰函数微粒群寻优算法.pdf

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