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Study on air combat tactics decision-making based on bayesian networks

机译:基于贝叶斯网络的空战战术决策研究

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Air combat tactics decision-making is a procession which full of complexity and uncertainty. The decision-making is uncertainty fusion reasoning with multi-sensors system. Aim to deal with the uncertainty in a dynamic decision-making process of air combat, bayesian network model of air combat tactics decision-making has been brought out based on the merits of bayesian networks on uncertainty reasoning. Firstly, the air combat tactics of beyond visual range (BVR) was analyzed in detail as a typical air combat example based on the combat situation of both sides. Secondly, the decision-making variables and reasoning rules were selected based on the tactics control mathematics model. Lastly, according to the decision-making variables and the reasoning rules, the bayesian networks model of BVR combat tactics decision-making was given out. Then the optimal tactics decision-making can be selected applied with the bayesian network inference algorithm. The method has been tested with given conditions. The simulation results have showed that the tactics decision-making models could improve the decision-making accuracy and intelligent and the algorithm is simple, perspicuity and apt realization.
机译:空战战术决策是一个充满复杂性和不确定性的队伍。决策是采用多传感器系统的不确定性融合推理。为了解决空战动态决策过程中的不确定性,基于贝叶斯网络在不确定性推理上的优点,提出了空战战术决策的贝叶斯网络模型。首先,根据双方的作战情况,详细分析了超视距空战战术(BVR),将其作为典型的空战实例。其次,根据战术控制数学模型选择决策变量和推理规则。最后,根据决策变量和推理规则,提出了BVR作战战术决策的贝叶斯网络模型。然后可以采用贝叶斯网络推理算法选择最优策略决策。该方法已在给定条件下进行了测试。仿真结果表明,该策略决策模型可以提高决策的准确性和智能性,算法简单,明了,易于实现。

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