Neural Network Method for Ballistic Parameters Design Taking Uncertainty into Account

摘要：

To investigate the effect of design parameters with uncertainty characteristics on performance in ballistic design, neural network method was adopted to determine optimized standard deviations of corresponding parameters. A trajectory model was established first and Monte Carlo simulation was done to analyze statistical performance of the flight range, which is used as the objective. By controlling distribution variances of parameters using a neural network approach, Circular Error Probability (CEP) is limited within a satisfactory range and therefore precision is improved.

关键词： neural network uncertainty circular error probability ballistics

作者: Changqing Liu Wencai Luo

作者单位: college of aerospace and materials engineering national university of defense technology Changsha, China

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 93-96

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）