摘要
粒子群优化算法是根据鸟群觅食过程中的迁徙和群集模型而提出的用于解决优化问题的一类新兴的随机优化算法.介绍了PSO算法的基本原理和一些改进措施及PSO算法的应用,并对其将来的发展进行了展望.
Particle swarm optimization is put forward according to the simulation of migration of bird flock in their food-searching and the group model, and is a novel stochastic optimization algorithm which can be used to solve optimization problems. In this paper, particle swarm optimization algorithm principles, some amehorative steps and some applications of the algorithm are introduced, and the outlook for future research on this algorithm is presented.
出处
《重庆工学院学报》
2007年第9期79-81,90,共4页
Journal of Chongqing Institute of Technology
基金
河南省自然科学基金资助项目(2004924075)
河南省科技攻关项目(0524480009)
关键词
粒子群优化算法
群智能
神经网络
particle swarm optimization
swarm intelligence
neural network
