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基于扩展贝叶斯方法融合的作战效能评估研究
引用本文:黄炎焱,杨峰,雷震,王维平.基于扩展贝叶斯方法融合的作战效能评估研究[J].系统仿真学报,2007,19(4):856-860,864.
作者姓名:黄炎焱  杨峰  雷震  王维平
作者单位:国防科技大学信息系统与管理学院,长沙,410073
摘    要:从多个视角采集评估数据源并进行武器装备的作战效能评估,是一种提高评估结果可信度的做法。在武器装备论证阶段,评估数据源主要来自专家经验和仿真结果,但因这两种数据源的差异太大,难以进行直接的评估聚合。为此,提出采用信念图模式统一两者的数据表达,再采用一种扩展的贝叶斯推理算法进行评估融合,最后得到评估装备的综合作战效能。以装甲主战装备改进型的作战效能评估为例进行验证,结果表明该方法符合评估实际,是一种有意义的新方法。

关 键 词:作战效能评估  专家数据  仿真数据  融合  信念图  扩展贝叶斯方法
文章编号:1004-731X(2007)04-0856-05
收稿时间:2005-12-05
修稿时间:2005-12-052006-09-06

Evaluation Method of Weapon Equipment Operational Effectiveness Based on Extensive Bayesian Algorithm Fusion
HUANG Yan-yan,YANG Feng,LEI Zhen,WANG Wei-ping.Evaluation Method of Weapon Equipment Operational Effectiveness Based on Extensive Bayesian Algorithm Fusion[J].Journal of System Simulation,2007,19(4):856-860,864.
Authors:HUANG Yan-yan  YANG Feng  LEI Zhen  WANG Wei-ping
Institution:School of Information System and Management of National University of Defense Technology, Changsha 410073, China
Abstract:It is a right way to improve the credibility of evaluation results of the weapon equipment operational effectiveness(WEOE) by means of correcting and fusing the data from many viewpoints.At the stage of the equipment demonstration,the data of evaluation mainly come from expert belief and simulation results,but these data can not be directly used to evaluate the WEOE because these two kinds of data are very different in form and in attribute.And therefore,the Belief Map Expression mode was put forth to uniform the expression of these different data,and an extensive Bayesian Pattern was made to fuse the different evaluation data so as to get the final evaluation results of the WEOE.By means of above method,an example about the improved types of armored equipments were evaluated on their operational effectiveness,and the evaluation results show that this method is fit for the practical equipments demonstration,so it is a new promising method.
Keywords:operational effectiveness evaluation  expert data  simulation data  fusion  belief map  extensive Bayesian algorithm
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