摘要
目的为了求解解析性质差的复杂优化问题,提出了一种新的交叉粒子群算法。方法该算法将全局邻域粒子群算法与局部邻域粒子群算法交叉使用,并采用适应度距离比确定局部邻域粒子群算法的速度更新策略。结果提高了粒子群算法粒子的搜索能力。结论该算法用来解决六边形阵列天线问题,取得了满意的效果。
Aim To deal with the complex optimization problem without good analysis property, a new crossed Particle Swarm Optimization（PSO） algorithm is proposed. Methods The new algorithm intersects two different PSO algorithms： global neighbor PSO and local neighbor PSO. The fitness distance ratio（FDR） is selected to update the velocity of the local PSO. Results The performance of the particle of PSO is boosted. Conclusion The new algorithm is used to design the hexagon antenna array, and obtain some favorable results.
出处
《宝鸡文理学院学报（自然科学版）》
CAS
2008年第3期199-202,共4页
Journal of Baoji University of Arts and Sciences(Natural Science Edition)
关键词
粒子群优化
局部领域算法
适应度距离比
六边形阵列天线
particle swarm ptimization（PSO）
local neighbor PSO
fitness distance ratio（FDR）
hexagon antenna array
