摘要
文章在遗传算法(GA)和粒子群算法(PSO)的基础上,介绍了GA-PSO组合算法的流程和模态修正适应度函数的确定,并利用该算法对一个5层钢架结构模型进行修正,证实了该算法能有效修正模型。该算法能在前期利用GA算法进行高效全局搜索,后期利用PSO算法进行细致局部搜索,与单独使用PSO算法和GA算法相比,该组合算法修正效率和精度更高。
The paper presents the computation flow of GA-PSO(Genetic Algorithms-Particles Swarm Optimization) hybrid algorithm and the fitness function determination for modal updating based on GA(Genetic Algorithms) and PSO(Particles Swarm Optimization) algorithms.A five-layer steel frame construction is used as an example and it is shown that this method enjoys a high efficiency.The GA-PSO algorithm uses the GA to efficiently search for the global-optimization solution at an early stage, and on the basis of the GA solution, the PSO algorithm is used to intensively search for the local-optimization solution at a later stage.Comparing with the PSO and GA, GA-PSO algorithm enjoys higher updating efficiency and precision.
出处
《航天器环境工程》
2009年第4期383-385,404,共3页
Spacecraft Environment Engineering
基金
"微小型航天器系统技术"长江学者创新团队发展计划课题
关键词
遗传算法
粒子群算法
组合算法
模型修正
genetic algorithms
particles swarm optimization
hybrid algorithm
model updating