基于M-C的高维SEA方法  

High-dimensional SEA Method Based on M-C

作　　者：胡新刚[1] 罗云峰[1] 王明哲[1] 

机构地区：[1]华中科技大学自动化学院,武汉430074

出　　处：《兵工自动化》2016年第2期5-9,共5页Ordnance Industry Automation

基　　金：国家自然科学基金(61273207)

摘　　要：针对高维指标的系统效能分析(system effectiveness analysis,SEA)方法的应用难点,在系统数值仿真的基础上研究高维性能指标联合概率密度函数拟合,通过将联合概率密度函数应用于计算高维数值积分的蒙特卡罗平均值方法中,得到一种解决SEA中高维性能指标效能分析的蒙特卡罗数值方法,并用实例进行验证评估。结果表明:该方法是有效、实用的,能为SEA方法中涉及高维指标的分析提供一种行之有效的方法。For the difficult issue of high-dimensional metrics system effectiveness analysis（SEA） applications, based on the numerical simulation of the system, a high-dimensional performance indicators joint probability density function fitting method was presented in this paper firstly. And then, the joint probability density function was used to calculate high-dimensional numerical integration of the Monte Carlo average value method, looking forward to getting a Monte Carlo numerical method of SEA to solve effectiveness analysis of high-dimensional performance metrics. Finally in the paper, the method was verified and evaluated by an example of air intruder model（AI）. The results show that the method is effective and practical, and give an effective method for the high-dimensional metrics analysis in the SEA.

关 键 词：高维指标 概率密度 SEA 蒙特卡罗 

分 类 号：TJ02[兵器科学与技术—兵器发射理论与技术]