基于Vague集的二阶不确定性决策融合模型

Modeling Decision Fusion in Second-Order Uncertainty Based on Vague Set

针对广义传感器使用所产生的弱知识环境下不确定信息决策融合问题,给出了基于二阶Vague集的不确定信息的融合模型.通过数据示例演示了方法操作过程,并从不确定性来源、数据、模型、性能等方面讨论了本算法的先进性.结果表明,方法在二阶不确定决策融合中具有准确度高、稳定性好、容错能力强等优点.

Focused on the second-order uncertainty （SOU） issues in a weak knowledge envi- ronment which comes from generalized or ubiquitous sensors, a novel method of fuzzy decision fusion was presented based on Vague set. An example was employed to show how to use the method. Then a further discussion was opened up about the advantages of the method from different scopes such as the origin of the SOU, the data style, the model and the computational capability. It was proved that the method was exact. robust and powerful.