摘要
将神经网络理论引入火控领域,建立一个输入参数为高度H、速度V和俯冲角λ的多层神经网络模型,用B-P学习算法,对弹道的射程A和落下时间T进行拟合。仿真结果表明,神经网络是用于弹道参数拟合的一个有效的方法,并取得了满意的精度。
In this paper, the nurtificial neural network theory is introduced into the fire control field,and established a multi-layered Neural Network model with the input parameters of altitude H ,velocity V and dive angle λ,the B-P learning algorithm is used to approach the range A and fall down time T of the trajectory. Simulation result shows,that Artificial neural network is a powerful tool for trajectory parameter approach with satisfactory accuracy.
出处
《火力与指挥控制》
CSCD
北大核心
1995年第2期69-72,共4页
Fire Control & Command Control
关键词
外弹道学
弹道参数
神经网络
算法
neural network,B-P algorithm,trajectory parameter