摘要
针对解决实际工程问题中,传统方法求解非线性方程组时对于初始值依赖性大的缺点,提出了改进的粒子群优化算法(pso),用混沌初始化替代随机初始化,使用谱系聚类法来避免早熟现象发生,根据聚类结果对粒子的速度进行更新,并应用于求解非线性方程组中,数据结果表明该方法提高了解的精确度,算法稳定性好.
For solving practical engineering problems and the traditional method for solving nonlinear equations for the shortcomings of the initial value dependent, an improved particle swarm optimization （PSO） was proposed. Alternative random initialization using chaotic initialization to avoid premature phenomenon occurs, the speed of the particle is updated according to the clustering results with hierarchical clustering analysis method and applied to solve nonlinear equations. The results show that the method can improve the understanding of the accuracy and has good stability of the algorithm.
出处
《吉林化工学院学报》
CAS
2013年第5期114-116,共3页
Journal of Jilin Institute of Chemical Technology
关键词
粒子群优化算法
混沌
谱聚类
非线性方程组
particle swarm optimization algorithm
chaos
spectral clustering
nonlinear equations
