摘要
雷达装备战场损伤信息是一个动态传播和更新过程,多组(部)件战场损伤修复顺序的优化能够提高战场抢修的效率.利用贝叶斯网络能够充分综合先验概率和后验概率的特点,在已有的装备类似案例、专家经验与现场的实际损伤情况等信息的基础上进行判定,具有完备性.根据雷达装备的结构特征,以最小预期代价为目标,构建和分析基于贝叶斯网络的战场损伤修复优化模型,提出了组(部)件损伤修复顺序的策略算法,具有一定的参考价值.
The battlefield damage repair（BDR） of radar equipment is a dynamic disseminating and updating process,and the efficiency of rush-repairing battlefield can be boosted by optimizing the BDR sequence of multi-components or parts.In this paper,by taking advantages of Bayesian network that can synthesize priori probability and posteriori probability to the full,the decision is made in terms of similar cases of the existing equipment,experts experience,the spot damaged situation and other information,achieving its completeness.According to the configuration characteristic of radar equipment an optimization model based on the BDR of Bayesian network is structured and analyzed,targeting the least expectation cost,and the strategic algorithm for components or parts damage repair sequence is presented,providing a certain reference for engineering.
出处
《空军雷达学院学报》
2011年第1期9-11,共3页
Journal of Air Force Radar Academy
基金
国家部委级资助项目
关键词
雷达装备
战场损伤修复
顺序优化
修复决策
贝叶斯网络
radar equipment
battlefield damage repair（BDR）
sequence optimization
repair decision-making
Bayesian network
