摘要
将粒子群优化(PSO)算法引入到发动机模型的求解中,利用粒子群优化算法所具有的群体智能和记忆功能,能够较快地求解模型,克服了N-R法求解发动机模型时对初值的敏感以及需要函数求导的困难。计算结果表明,粒子群优化算法求解发动机模型比N-R法具有更好的收敛性和更高的精度。
In this paper, a PSO algorithm which has swarm intelligence and memorial function is used to replace a Newton -Raphson method, which is sensitive to initial values and needs differential coefficient of functions. The results show that the PSO solves the model more precisely than N -R Algorithm.
出处
《航空计算技术》
2007年第6期39-41,44,共4页
Aeronautical Computing Technique
关键词
粒子群优化算法
航空发动机
数学模型
particle swarm optimization
aeroengine
mathematical model
