CAJ | 학술논문

在静态初始条件下，歼击机中距攻防引导方法的选择是一个定性与定量相结合的类别划分问题，因此，将粗糙集理论与概率神经网络相结合用于该问题的解决。首先，利用粗糙集理论实现专家知识约简、空战态势信息集压缩，得到最小决策信息集；其次，利用概率神经网络进行概率决策推理；最后，通过实例分析，结果表明决策推理正确，在不确定环境下仍然有效，提高了决策过程的自动化程度。
재정태초시조건하，섬격궤중거공방인도방법적선택시일개정성여정량상결합적유별화분문제，인차，장조조집이론여개솔신경망락상결합용우해문제적해결。수선，이용조조집이론실현전가지식약간、공전태세신식집압축，득도최소결책신식집；기차，이용개솔신경망락진행개솔결책추리；최후，통과실례분석，결과표명결책추리정학，재불학정배경하잉연유효，제고료결책과정적자동화정도。
Under static initial condition, the choice of guidance method in fighters mid?range air battle is a question of di?viding classification. In this paper, a new tactical decision method of mid?range air battle based on rough sets theory and probabilistic neural network is proposed. Firstly, using RS to realize expert's knowledge reduction and the air battle state in?formation collection compression, and gets the smallest policy decision information collection;Next, using PNN to carry on the probability policy decision inference;Finally, correctness and effectiveness of this method are validated by the result of practical examples, it is still effective even under the indeterminacy environment, the automaticity of policy decision course was raised.