摘要
针对直觉模糊贝叶斯网络模型在对网络证据节点的信息描述中存在隶属度和非隶属度单一且未能充分考虑犹豫度的问题,提出了基于对偶犹豫模糊贝叶斯网络的威胁评估方法。首先,将直觉模糊集扩展到对偶犹豫模糊集,使得对节点信息的模糊性和不确定性有了更贴近实际和更全面准确的描述;其次,通过改进的Dα算子将对偶犹豫模糊集中犹豫度重分配给隶属度和非隶属度并作为网络证据节点的输入;然后,分析了影响威胁评估的因素并建立了贝叶斯网络模型;最后,根据实时战场数据对目标威胁度进行结果预测与分析,仿真结果表明,该方法可以准确有效地评估出敌方对我方的威胁度。
In the information description of intuitionistic fuzzy Bayesian network model to the network evidence node,there is only single membership degree or non-affiliation degree,and the hesitation degree is not taken into full consideration.To solve the problem,a threat assessment method based on dual hesitant fuzzy Bayesian network is proposed.Firstly,the intuitionistic fuzzy set is extended to the dual hesitant fuzzy set,makes the ambiguity and uncertainty of the node information more realistic,more comprehensive and accurate.Secondly,through the improved D_α operator,the dual hesitation of the hesitation of the hesitation is assigned to the membership degree and the non-affiliation degree,which is used as the input of the network evidence node.Then,analysis is made to the factors affecting the threat assessment and a Bayesian network model is established.Finally,based on the real-time battlefield data,the target threat degree is predicted and analyzed.The simulation results show that the method can accurately and effectively evaluate the threat of the enemy.
作者
邱少明
王健
杜秀丽
陈波
QIU Shaoming;WANG Jian;DU Xiuli;CHEN Bo(Dalian University,Key Laboratory of Communications and Network,Dalian 116622,China;School of Information Engineering,Lingnan Normal University,Zhanjiang 524048,China)
出处
《电光与控制》
CSCD
北大核心
2020年第11期33-38,共6页
Electronics Optics & Control
基金
装备发展部领域基金项目(6140001030111)。
关键词
威胁评估
贝叶斯网络
对偶犹豫模糊信息
Dα算子
threat assessment
Bayesian network
dual hesitant fuzzy information
Dαoperator
