基于EPSO-BP的Elman网络及其在飞行轨迹预测中的应用  

Elman network based on EPSO-BP and its application in flight trajectory prediction

作　　者：王俭臣[1] 齐晓慧[1] 单甘霖[2] 

机构地区：[1]军械工程学院无人机工程系,石家庄050003 [2]军械工程学院电子与光学工程系,石家庄050003

出　　处：《控制与决策》2013年第12期1884-1888,共5页Control and Decision

基　　金：国防预研基金项目(513270203);武器装备预研重点基金项目(9140A27020211JB3402)

摘　　要：针对BP训练方式采用梯度法易导致局部收敛的不足,提出一种融合进食粒子群算法(EPSO)和梯度法的Elman网络优化方法.首先,通过模拟鸟群进食行为得到一种EPSO算法,以改善标准PSO的全局性能;然后,将EPSO用于Elman网络权值的全局优化,同时将梯度法用于EPSO的进食过程局部搜索,以提高解的局部收敛性能;最后,将该网络优化方法用于飞行轨迹预测实验,仿真结果表明了其有效性.To overcome the local convergence shortcoming of the gradient method used by the BP approach in the Elman network training process, a combined training method of the exhaustion particle swarm optimization（EPSO） and gradient method is built. An enhanced PSO algorithm（EPSO）, which has better global property, is proposed by simulating feeding behavior of birds. Then, the EPSO algorithm is applied to optimizing Elman network weights across the whole solution space, and the gradient method is used in the exhaustion process of EPSO to improve the local convergence property. Finally, the proposed training method is applied to flight trajectory prediction experiment, and simulation results show the effectiveness of this method.

关 键 词：ELMAN网络 融合方法 进食过程 轨迹预测 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]