基于多源情报的陆军远程火力毁伤效果评估

为提高火力毁伤评估准确性，构建一种陆军远程火力毁伤效果评估模型。在分析目标毁伤情报源和构建毁 伤判据准则的基础上，以贝叶斯网络(Bayesian network)为理论基础，利用最大似然估计法(maximum likelihood estimate，MLE)和专家修正法确定模型的网络参数，求解毁伤等级评估公式，并结合实际数据证明模型的适用性。结 果表明：该模型能够准确评估陆军远程火力对打击目标造成的毁伤等级，为精准评估陆军远程火力毁伤效果提供支撑。

Assessment of Army Long-range Firepower Damage Effectiveness Based on Multi-source Intelligence

In order to improve the accuracy of firepower damage assessment, an army long-range firepower damage effectiveness assessment model was established. Based on the analysis of target damage information sources and the construction of damage criterion, the Bayesian network is taken as the theoretical basis, and the maximum likelihood estimate (MLE) and expert correction method are used to determine the network parameters of the model, and the damage level evaluation formula is solved, and the applicability of the model is proved by actual data. The results show that the model can accurately evaluate the damage level of the army''s long-range firepower to the target, and provide support for accurate evaluation of the army''s long-range firepower damage effectiveness.