摘要
提出了基于带收缩因子的粒子群优化(PSO-CF)算法求解二重数值积分的方法。PSO-CF算法初始时在积分区域内随机选取一定的分割点,粒子的速度采用收缩因子进行更新,粒子将朝着更好的位置移动。该算法基于分割后的每一个小矩形的4顶点和4内点及中心点定义适应值,用来评价粒子的优劣,通过反复迭代优化粒子。PSO-CF算法对最优粒子采用复化4内点公式计算二重数值积分。仿真实例表明,该算法积分精度较高,效果良好。
A new method was presented to calculate two dimentional numerical integration based on Particle Swarm Optimization（PSO） with a constriction factor,named PSO-CF.PSO-CF algorithm selected some initial partition points randomly in the domain,and used the constriction factor to update the velocity,then the particles would move towards better position.This algorithm evaluated particles by fitness value based on the four vertices,four interior points and the center point of every small rectangle after partition,it optimized the particles through repeated iteration.For the opitimal particle,PSO-CF algorithm used the composite four interior points to calculate two dimentional numerical integration.The experimental results show that integral precision is higher,and this method is effective.
出处
《计算机应用》
CSCD
北大核心
2011年第11期3094-3096,共3页
journal of Computer Applications
关键词
二重数值积分
优化
粒子群优化算法
收缩因子
代数精度
two dimensional numerical integration
optimization
Particle Swarm Optimization（PSO） algorithm
constriction factor
algebraic accuracy
