基于贝叶斯网络和直觉模糊推理的态势估计方法

将直觉模糊推理理论与贝叶斯网络推理相结合，提出一种基于直觉模糊理论和贝叶斯推理网络的态势估计方法。首先，分析当前贝叶斯网络推理的特点与不足，建立基于直觉模糊函数的贝叶斯网络推理模型；其次，证明直觉模糊函数在贝叶斯网络推理中是可传播的；最后，用实例给出评估结果，验证方法的有效性和模型的正确性。采用实例说明，当证据节点犹豫度较大时，一般贝叶斯网络推理得不到正确的结果，而该方法克服了此缺点，能够得到正确的推理结果。

Situation assessment method based on Bayesian network and intuitionistic fuzzy reasoning

By combining the theory of intuitionistic fuzzy reasoning (IFR) and Bayesian network (BN), situation assessment (SA) method based on IFR and BN is proposed. Firstly, with the analysis of the properties and vulnerabilities of BN,a model based on intuitionistic fuzzy function (IFF) and BN is established; secondly, IFF is tested to be transmitted in BN; finally,examples are given to verify the techniques for SA based on BN and IFR. The simulated results show that while the uncertain degree of evidence nodes is bigger,the normal BN can not get the right result but the techniques overcome this disadvantage and can get the right.