基于贝叶斯网络的编队对地攻击损伤评估研究

随着武器的高科技化、战场环境的复杂化、战斗节奏的加快,战斗损伤评估系统在现代战争中占有越来越重要的地位。针对战场战斗损伤评估信息的多样性、不确定性和模糊性,基于贝叶斯网络易于进行不确定性推理的优点,提出应用贝叶斯网络对对地攻击效果进行分析评价,建立了编队对地攻击损伤评估的贝叶斯网络模型,给出了基于贝叶斯网络的损伤评估的推理决策方法,并且对该方法进行了仿真分析。仿真实例表明,基于贝叶斯网络的损伤评估模型能够提高损伤评估的准确度,而且推理简单,易于实现。

Damage assessment of formation air-to-ground attack based on Bayesian networks

Battle damage assessment system is important in modern combat along with high-tech of weapon,complexity of battlefield and quicken of combat rhythm.Aim at the diversity,uncertainty and illegibility of battle damage assessment data sources,based on the merit of Bayesian networks have advantages on deal with uncertainty inference,the Bayesian networks models of air-to-ground battle damage assessment has been built.The Bayesian inference algorithm has been given out.The simulation example of air-to-ground combat damage assessment also has been delt with Bayesian networks.The simulation results showed that the damage assessment models could improve the assessment accuracy and the algorithm is simple,perspicuity and apt realization.