合成分队火力分配自适应决策模型研究

针对合成分队武器和打击目标种类多样,战场态势变化迅速的特点,提出了一种火力分配自适应决策模型。该模型在火力分配中加入满意度函数以提高整体火力打击效率,根据各决策单元评估信息通过灰色关联法获得目标价值,根据目标类型和特点通过BP神经网络自动选择适合打击武器,通过GM(1,1)模型预测目标状态指标并结合相应的影响因素预测命中概率。仿真实例表明,自适应火力分配模型能够依据态势变化信息调整火力分配模型参数,获得更加合理有效的火力分配结果。

Research on Adaptive Decision Model of Fire Distribution of Synthetic Unit

Aiming at the variety of weapon and target species of the synthetic unit,and the characteristics of rapid change of the battlefield situation,an adaptive decision model of fire distribution is put forward. The model in the fire distribution added satisfaction function to enhance the overall firepower efficiency,according to each Decision Making Unit (DMU)assessment information through gray correlation method obtained value goal,according to the types and characteristics of the target by BP neural network automatically select suited combat weapons,based on GM (1,1)model to predict the target state index and combined with the corresponding factors predict hit probability. The simulation results show that the model can adjust the parameters of the fire distribution model based on the situation information and get more reasonable and effective fire distribution results.