基于贝叶斯网络的辐射源威胁等级评估算法

贝叶斯网络是近年来人工智能领域最重要的研究成果之一，在具有不确定性的推理和决策问题中得到了广泛的应用。以贝叶斯网络及其推理机制为基础，主要研究了贝叶斯网络在辐射源威胁等级评估方面的应用。选取了部分影响因素，建立了基于贝叶斯网络的辐射源威胁等级评估模型。最后通过一个计算机仿真实例验证了算法具有连续性和累积性，能够对辐射源威胁等级做出较准确评估。

Algorithm of Emitter Threat Level Assessment Based on Bayesian Networks

As one of the most important harvest in AI field this years,Bayesian networks is widely used in uncertain problem's reasoning and decision-making.After the theory and inference mechanism of Bayesian networks was introduced,this paper mainly studies the application of Bayesian networks in emitter's threat level assessment.A model based on Bayesian networks is provided.It can be proved by an simulation instance that the algorithm has the ability of accumulate history information and is effective to reflect the real threat level of emitter.