基于模糊神经网络模型对射手的评价(英文)  

Estimation on Shooter Based on Fuzzy Neural Net Model

作　　者：王晓芳[1] 林海[1] 

机构地区：[1]北京理工大学宇航科学技术学院,北京100081

出　　处：《系统仿真学报》2008年第19期5415-5418,共4页Journal of System Simulation

基　　金："11th Five-Year Plan" Advanced Research Foundation

摘　　要：在图像制导导弹中,射手经常参与识别、捕获目标以及控制导弹跟踪、攻击目标。为评价一个射手,通过增加输入和输出论域的模糊子集数,对普通的射手模糊神经网络模型进行了改进。基于改进的射手模糊神经网络模型,提出了两种评价射手的方法。仿真结果表明:两种方法都能够有效地比较和评价射手,为选择和训练射手提供了依据。In the system of image guided missile, shooter often needs to acquire, capture target and control missile to trace, attack target. To estimate a shooter, common fuzzy neural net （FNN） shooter model was improved by increasing the number of fuzzy subsets defined on the universe of discourse of input and output. Two methods based on the improved FNN shooter model were proposed Simulation results show that both of the methods can compare and estimate shooter effectively, which is helpful for choosin~ and training shooter.

关 键 词：图像制导导弹 射手 模糊神经网络模型 评价 

分 类 号：TJ765.2[兵器科学与技术—武器系统与运用工程]